Published Ahead of Print on February 26, 2016, as doi:10.3324/haematol.2015.139139.
Copyright 2016 Ferrata Storti Foundation.
Metabolic pathways that correlate with post-transfusion
circulation of stored murine red blood cells
by Karen de Wolski, Xiaoyun Fu, Larry J. Dumont, John D. Roback, Hayley Waterman,
Katherine Odem-Davis, Heather L. Howie, and James C. Zimring
Haematologica 2016 [Epub ahead of print]
Citation: de Wolski K, Fu X, Dumont LJ, Roback JD, Waterman H, Odem-Davis K, Howie HL,
and Zimring JC. Metabolic pathways that correlate with post-transfusion circulation of stored murine
red blood cells. Haematologica. 2016; 101:xxx
doi:10.3324/haematol.2015.139139
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Metabolic pathways that correlate with post-transfusion circulation
of stored murine red blood cells
Karen de Wolski, Xiaoyoun Fu 1,3 , Larry J. Dumont 4, John D. Roback 5, Hayley Waterman,
Katherine Odem-Davis1, Heather L. Howie1, James C. Zimring 1,2,3
1.
Bloodworks NW Research Institute, Seattle, WA 98102
2.
University of Washington Department of Laboratory Medicine and Department of Internal
Medicine, Division of Hematology, Seattle, WA
3.
University of Washington Department of Internal Medicine, Division of Hematology, Seattle,
WA
4.
Geisel School of Medicine at Dartmouth, , Lebanon, NH
5.
Department of Pathology and Laboratory Medicine, Emory University School of Medicine,
Atlanta, GA
*To whom all correspondence should be addressed
Conflicts of Interest: J.C.Z. and Bloodworks NW has intellectual property filed on material in this
manuscript. There are no other author conflicts relevant to this manuscript.
Please address correspondence to:
James C. Zimring, M.D., Ph.D.,
BloodworksNW Research Institute,
1551 Eastlake Ave E, Seattle,
WA 98102 USA- E-mail: [email protected]
Running Head: Metabolic Predictors of RBC Storage in Mice.
1
Abstract:
Transfusion of red blood cells is a very common inpatient procedure, with more than 1 in 70
people receiving a red blood cell transfusion annually (in the USA). However, stored red blood
cells are a non-uniform product, based upon donor-to-donor variation in red blood cell storage
biology. While thousands of biological parameters change in red blood cells over storage, it has
remained unclear which changes correlate with function of the red blood cells, as opposed to
being co-incidental changes.
In the current report, a murine model of red blood cell
storage/transfusion is applied across 13 genetically distinct mouse strains and combined with
high resolution metabolomics to identify metabolic changes that correlated with red blood cell
circulation post-storage. Oxidation in general and peroxidation of lipids in particular, emerged
as changes that correlated with extreme statistical significance, including generation of
dicarboxylic acids and monohydroxy fatty acids.
In addition, differences in anti-oxidant
pathways known to regulate oxidative stress on lipid membranes were identified.
Finally,
metabolites were identified that differed at the time the blood was harvested, and predict how
the red blood cells perform after storage, allowing the potential to screen donors at time of
collection.
Together, these findings map out a new landscape in understanding metabolic
changes during red blood cell storage as they relate to red blood cell circulation.
2
Introduction:
Transfusion of stored red blood cells (RBCs) is amongst the most frequent inpatient
therapies; for example, in the United States, approximately 1 out of every 70 people are
transfused each year. However, while the process of RBC collection, storage, and transfusion
is well-controlled, there remains substantial variability in the quality of RBC units, presumably as
a result of varying donor characteristics (1).
It is understood that some donors’ RBCs
consistently store poorly, and there are currently no methodologies to identify such donors
(other than autologous
51
-Cr survival studies) (1).
Thus, measuring and standardizing the
quality of stored RBCs remains elusive.
The biological changes that occur during RBC storage, collectively called the “storage
lesion” consist of myriad cellular and biochemical alterations (2, 3). While the catalogue of
changes known to occur with RBC storage continues to grow into the thousands (with the
application of omics technologies), it remains unclear which changes correlate to clinical
performance of transfused RBCs and which are coincidental. Both historical and more recent
data have demonstrated that RBC changes during storage and the underlying metabolism of
RBCs are both heritable traits in humans (4-9).
Much attention has been paid in recent years to the concern that transfusion of longer
stored RBC units may result in worse medical outcomes. These concerns are fueled, largely,
based upon numerous retrospective studies reporting such an effect (10). Recently, several
randomized controlled trials, in particular clinical settings, have been completed, and no
difference was observed between groups (11-13).
There remains considerable debate
surrounding this issue (14). However, this issue is unrelated to the goal of providing the best
RBC units available, and to storing RBCs so as to generate the most efficacious product. The
goal of the current study is to elucidate donor biology that affects RBC storage, and the ability of
the RBC to circulate post-transfusion.
3
To identify biochemical components of the storage lesion that are correlated with RBC
performance, in particular the ability of stored RBCs to circulate post-transfusion, we analyzed
13 commonly available inbred strains of mice. Herein, we report significant variation amongst
strains, both with respect to post-transfusion recoveries of stored RBCs and also the basic
metabolomics of stored RBCs.
Moreover, significant correlations between biochemical
pathways and RBC storage are identified. In particular, lipid metabolism and oxidation (and
underlying anti-oxidant pathways), emerged as a dominant theme in differences in RBC storage
from genetically distinct murine donors. Together, these findings help to distinguish biochemical
components of the storage lesion that correlate with RBC function in a mouse model. These
studies provide mechanistic insight into the biology of RBC storage, define the landscape of
murine specifics for ongoing basic research, and also highlight novel hypotheses to provide a
rational basis for subsequent human studies.
4
Methods:
Mice: The following strains of mice were purchased from Jackson Labs (Bar Harbor, ME):
KK/HIJ, LG/J, AKR/J, FVB/NJ, C3H/HeJ, DBA/2J, NOD/ShiLtJ, 129X1/SvJ, 129S1/SvImJ, A/J,
BTBR/ T+ tf/J, Balb/cByJ, C57Bl/6J). All were female and used for blood donation at 12-15
weeks of age. UbiC-GFP male mice, which are on a C57BL/6 background, were bred to FVB/NJ
females in the Bloodworks NW Research Institute (BWNWRI) Vivarium and offspring were used
as RBC recipients at 24-28 weeks of age. HOD mice, used as a fresh tracer population for
transfused RBCs, were likewise bred in the BWNWRI Vivarium. The HOD mouse was first
described on an FVB background (15), but has now been backcrossed onto C57BL6J for
greater than 20 generations. All mice were maintained on standard rodent chow and water in a
temperature- and light-controlled environment. All experiments were performed according to
approved Institutional Animal Care and Use Committee (IACUC) procedures.
Collection and Storage of Blood: Whole blood (600 µl) was collected via cardiac puncture into
84 µl CPDA-1 (12.3%) in a sterile 1.7 ml snapcap microcentrifuge tube. Hematocrits were
adjusted to approximately 75% (by removal of supernatant) and samples were stored
Eppendorf tubes for seven days at 4ºC.
in
After storage, 50 µl stored RBCs were resuspended in
510 µl PBS and 5 µl of fresh HOD packed RBCs were added to the suspension as an internal
control. The mixture of RBCs was then directly transfused into FVB/NJ x UbiC-GFP recipients
by intravenous tail vein injection. The remaining sample of stored RBCs was snap frozen in
liquid nitrogen for future metabolomics analysis. Ratios of donor blood to HOD tracer RBCs
was enumerated, both at baseline in the cells to be transfused (pre-transfusion mixture) and
also in peripheral blood acquired from recipients 24 hours after transfusion (post-transfusion
samples collected into ACD). Pre-transfusion and post-transfusion RBCs were washed 3X with
PBS, and stained for 30 mins with 0.5µg anti-Fy3 (clone MIMA29) in 50µl PBS. Stained cells
5
were then washed 3X with PBS and incubated with 0.2µg APC Goat-anti-mouse Igs (BD Cat.
550826) in 50µl PBS for 30 mins, which stains RBCs bound with MIMA-29 and thus identifies
HOD tracer RBCs. Cells were then washed 3 times, re-suspended in PBS, and analyzed by flow
cytometry (500 HOD+ events were counted for each sample). This approach utilizes MIMA29
to stain HOD tracer RBCs with a color that is different than the GFP RBCs, which fluoresce
spontaneously.
Forward and side scatter were used to exclude fragmented or lysed RBC
fragments, such that counts reflected intact RBCs. Final RBC survival was calculated by the
formula:
(Circulating Stored RBC/HOD RBC of post-transfusion sample) / (Stored RBC/HOD pretransfusion sample).
For experiments studying “fresh RBCS”, the RBCs were collected and processed identically to
stored RBCs, with the only difference being they were used after collection and without further
storage.
Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS):
and Gas Chromatography-Mass Spectroscopy (GC-MS): Please see supplemental methods for
details. Mass Spec was carried out by a commercial vendor (Metabolon Inc., NC, USA).
Statistics: Comparisons between strains of recoveries were performed separately on each
experiment using one-way ANOVA followed by Tukey’s multiple comparisons test, with a single
pooled variance.
In the case of stored RBCs, the data were first log10-transformed to
approximate a normal distribution; the data from the fresh RBCs required no data
transformation.
Analyses were performed using Graphpad PRISM 6 software.
Linear
correlations were summarized by Pearson’s coefficient with p-values by F-tests and q-values to
account for multiple testing in the evaluation of statistical significance.
6
Results:
Strain Dependent Variation in Post-Transfusion Recoveries of Stored RBCs
To test the genetic variation in RBC storage phenotype amongst mice, a panel of inbred
strains was analyzed.
These strains were chosen due to commercial availability, well
characterized biology and resolved genetic sequence.
Consideration was also given to
sampling different phylogenetic arms (see Figure 1A.). A well-characterized murine model of
RBC storage was utilized (16), with minor modifications (see methods). RBCs from each of the
indicated test strains were collected, processed, and either transfused as “fresh” RBCs, or
stored for 7 days. The post-transfusion circulation of test RBCs, 24 hours after transfusion (24hr recoveries), was determined by transfusing test RBCs into GFP-F1 recipients and
enumerating GFP negative populations in peripheral blood 24 hours post-transfusion. This
approach allows analysis of RBC recoveries without having to risk altering the RBCs through
any labeling procedure. To isolate donor biology as a variable, a single common transfusion
recipient was utilized for all donor strains; in particular an F1 cross between UbiC-GFP and FVB
mice (GFP-F1). RBCs from UbiC-GFP mice express high levels of green fluorescent protein
(GFP) in RBCs and are on a C57BL/6 background. Thus, the GFP-F1 mice are heterozygous
at all loci between B6 and FVB mice, and have a GFP transgene.
To control for differences in transfusion volume and phlebotomy, and also to allow
enumeration on a cell by cell basis, a “fresh tracer” control RBC population was added to each
test RBC population prior to transfusion (Figure 1B – left panel).
The tracer population
consisted of HOD RBCs, which express an easily detectable transgene on RBCs. Essentially
no GFP negative events are observed in untransfused recipient mice (Figure 1B – middle
panel)). The ratio of test RBCs to tracer RBCs 24 hours after transfusion (Figure 1B –right
7
panel) was then corrected to the pre-transfusion ratio.
Recoveries were evaluated for each
strain for both 7 days of storage and in freshly isolated RBCs.
Three independent experiments were performed for stored RBCs from each of the
indicated strains, and the results of each experiment are shown (Figure 1C). Whereas there
was relative consistency in a given strain across experiments, there was substantial strain-tostrain variability in RBC recoveries after storage; no statistically significant differences in 24 hr
recoveries were observed from freshly isolated samples from the 13 different strains (Figure
1D). Extensive ANOVA comparisons between each strain, for both stored and fresh RBCs,
were performed and multiple differences of statistical significance were noted only for stored
RBCs (supplemental table 1).
General Metabolomic Analysis of Strain Variation in RBC Storage
For each experiment, prior to transfusion, a sample of the RBCs was snap-frozen.
Samples were subsequently subjected to analysis of metabolites by LC-MS/MS, resulting in the
resolution and relative quantification of 520 compounds of known identity. Principal component
analysis (PCA) showed a clear distinction between fresh and stored RBC samples within each
of the 13 mouse strains, as a function of the RBC metabolome (Figure 2). In addition, fresh
samples from the C57Bl/6J strain demonstrated limited segregation from the general sample
groupings and suggest that this strain may exhibit a baseline metabolic profile that further
differentiates it from other strains. However, there was otherwise no clear distinction in general
metabolomes between strains as a function of storage.
Glucose Metabolism of RBC Storage Across Inbred Mouse Strains
8
Analysis of RBC storage has traditionally focused on generation of ATP as a necessary
energy source for maintenance of RBC physiology. In addition, much attention has been paid to
generation and maintenance of 2,3-DPG, due to its ability to regulate oxygen affinity by
hemoglobin.
Analysis of glycolytic metabolites across strains demonstrated decreases in
glucose during storage in all cases (Figure 3A).
Likewise, in all strains, 2,3-DPG dropped
substantially at 7 days storage (Figure 3B). The endpoint of glycolysis (lactate) had a similar
increase in stored RBCs from each strain (Figure 3C). ATP was not detected as a metabolite
by this approach, and thus was not assessed in the current study.
Metabolites and Pathways that Correlate with RBC Storage
To investigate which metabolites (and metabolic pathways) may be associated with the
ability of RBCs to survive post-transfusion, metabolites in stored RBC units were chosen based
upon the following criteria (correlation greater than 0.5 or less than -0.5, p value <0.05, q value
<0.01) [see Supplemental Table 2 for a full list of compounds].
Using these criteria, 11
metabolites had a positive correlation with RBC storage (Supplemental Table 2, Stored RBCs,
Positive Correlation), 9 of the 11 metabolites identified were lipids, although various lipid
subspecies were identified, including free fatty acids (polyunsaturated, and monohydroxy),
lysolipids, and glycerol species.
Also noted was vitamin E (alpha-tocopherol), a common
cellular anti-oxidant most involved with oxidative stress in the lipid compartment. 12-HETE is an
arachidonic acid (AA) metabolite that has biological properties. Finally tryptophan was noted.
As examples of the typical distributions, both of the fatty acids docosapentaenoate (DPA) and
docosahexaenoate (DHA) showed a pattern (in general) of decrease over storage in strains that
stored poorly and increase in storage of strains that stored well (Figure 4A and 4C) resulting in a
positive correlation with final levels and 24-hr RBC recoveries (Figures 4B and 4D).
9
49 metabolites had a negative correlation with stored RBCs that fit the above criteria, the
majority of which were lipid species (Supplemental table 2, Stored RBCs, Negative Correlation).
Of these, 19 were either dicarboxylic acids (DCAs) or monohydroxy fatty acids (MHAs), known
to be associated with lipid oxidation and peroxidation, 10 of which had inverse correlations
greater than 0.80 with both p values and q values of less than 0.0001. In all of these cases,
levels were low at time of collection and increased over storage, to a greater extent in strains
that stored poorly. Representative box-plots of the relative amounts of a DCA (dodecanedioate)
and a MHA (16-hydroxypalmitate) are shown (Figure 4 E and G) along with the correlation plots
between these analytes and 24hr RBC recoveries (Figure 4F and H).
Of note, among the
MHAs identified are products with known biological function, including 13-HODE, 9-HODE and
the dihydroxy fatty acid, (9,10-DiHOME). In addition, 4-hydroxy-2-nonenal fit these criteria, and
is a well know product and mediator of lipid peroxidation (17). 5-HETE, which is an eicosanoid,
was also observed to have a similar pattern (Figure 4I and 4J). Of note, a related species (12HETE) showed an opposite correlation (Figures 4K and L), although to a less dramatic effect. 2
lysolipids and a monoacylglycerol were also observed (Supplemental table 2). In addition to
lipid species, negative correlates also included metabolites involved in glutathione metabolism
(4-hydroxy-nonenal-glutathione and methionine sulfoxide).
To test the hypothesis that baseline metabolite levels, present at time of blood collection,
would predict quality of RBC storage overtime, correlations were calculated between metabolite
levels in freshly collected RBCs and post-transfusion recoveries after storage (Supplemental
Table 2, Fresh RBCs). The same cut-offs of significance were used as above (correlation
greater than 0.5 or less than -0.5, p value <0.05, q value <0.01). 14 metabolites met these
criteria with regards to positive correlation, in a variety of pathways, including amino acid
metabolism, pyrimidine metabolism, and the urea cycle (Supplemental Table 2, Fresh RBCs,
Positive Correlation). Aspartate is presented as an example of a positively correlating analyte
10
(Figure 4M). 24 metabolites met the criteria with a negative correlation (Supplemental Table 2,
Fresh RBCs, Negative Correlation). Like the negative correlation of metabolites after storage,
a substantial clustering of fatty acid metabolites was observed, including 9 long chain fatty acids
of different composition, polyunsaturated fatty acids (linoleate and derivatives), and
monoacylglycerols. As an example, palmitate (16:1) is shown (Figure 4N).
In addition,
tocopherol, 4-hydroxy-nonenal-glutathione, and other amino acid metabolites were observed,
which is expanded on in the discussion of anti-oxidant pathways below.
Finally, correlations were analyzed for the fold change of a given analyte over storage by
calculating the ratio in fresh RBCs compared to 7 days of storage (Supplemental Table 2, Ratio
of Stored To Fresh).
The analysis of fold change reveals the same general patterns as
observed by analyzing data from 7 days of storage, with 17 ratios having a positive correlation
and 33 ratios having a negative correlation, which fit the same significance criteria as above. In
general, the same classes of compounds emerged, with a few notable differences discussed
below.
Analysis of Common Anti-Oxidant Pathways
Due to the preponderance of lipid peroxidation products, we analyzed differences in
common anti-oxidant pathways.
Alpha-tocopherol (vitamin E) is a major hydrophobic anti-
oxidant that mainly exerts its effects in lipid membranes. Levels of alpha-tocopherol in fresh
RBCs negatively correlated with recoveries of stored RBCs (Figure 5F; top panel). At the same
time, levels of alpha-tocopherol in stored RBCs positively correlated with recoveries (Figure 5F;
middle panel). In other words, the less alpha-tocopherol present at the time of collection and
the more alpha-tocopherol that remained after storage, the better the RBC recoveries. These
data are inconsistent with a simple model of increased alpha-tocopherol providing increased
11
resistance to oxidation. However, juxtaposition of starting and ending levels of alpha-tocopherol
showed that strains that stored poorly started with higher alpha-tocopherol levels than strains
that stored well; however, by the end of storage, strains that stored poorly had lower levels of
alpha-tocopherol than strains that stored well (Figure 5A). Strains that stored well had little
change in alpha-tocopherol at all, whereas poorly changing strains rapidly depleted their alphatocopherol. This trend becomes clear when the correlation(s) are analyzed with regards to the
ratio of alpha-tocopherol from fresh RBCs to stored RBCs (Figure 5F; bottom panel). These
data are equally consistent with poorly storing strains generating more oxidative stress, having
decreased anti-oxidant regeneration, or both.
Alternatively, alpha-tocopherol could represent
non-causal association and be a surrogate marker.
Although less dramatic than the pattern seen with alpha-tocopherol, GSH showed a
similar trend (Figures 5B and G). Since the most common anti-oxidant pathway of GSH is for 2
GSH molecules to form GSSG; GSSG levels were examined (Figure 5C); however, no obvious
pattern emerged to correlate with changes in GSH levels. In contrast, a clear trend was seen
with the analysis of 4-hydroxy-nonenal-glutatione, a common product of GSH anti-oxidant
activity upon a product of lipid peroxidation (Figure 5D).
Of note, increases in 4-hydroxy-
nonenal-glutathione from fresh RBCs to stored RBCs correlated with poor RBC recoveries (see
supplemental table 2, data not shown). Because vitamin C serves as an intermediate between
GSH and alpha-tocopherol, vitamin C levels were examined, but no meaningful trend was
observed (Figure 5E) and ascorbate levels did not correlate with RBC storage (data not shown).
Finally, although its correlation was 0.48 (and thus technically below the 0.5 cut-off), Nacetylcysteine (which is both an antioxidant and also a GSH precursor) had levels in stored
RBCs that correlated well with 24-hr RBC recoveries (Figure 5H).
12
Discussion:
The current report makes the observation that, similar to donor-to-donor variation in
storage of human RBCs, genetically distinct stains of mice have a wide range of RBC storage
biology regarding both metabolome and post-storage circulation. The ability of an RBC to
circulate does not guarantee its full function (e.g. traversing micocapillary beds, delivering
oxygen to tissues, removing CO2, etc.); however, it seems a fair statement that an RBC that
does not circulate will certainly not function. Thus, 24-hour recoveries are a meaningful, if not
all encompassing, metric and are currently used as licensing criteria for RBC storage systems.
The current studies are carried out in a tractable animal model; however, like all models
it suffers the potential that it may not translate into human biology. Nevertheless, it serves to
generate new knowledge of mammalian RBC storage biology, which may translate into humans,
and which provides (from amongst the numerous changes in RBCs during storage) a focused
list of compounds and pathways to test in human RBC storage. It is worth noting that lipid
peroxidation is a well-known component of storage of human RBCs (18-22).
In addition, a
number of studies have been reported regarding metabolomics of human RBCs, which show
heritable differences amongst donors and different storage conditions (6, 7, 23-27); to the best
of our knowledge no human studies have been reported that have combined metabolomics and
in vivo recoveries.
It is worth noting that the stored RBCs were not leukoreduced in the current study. The
majority of (although certainly not all) stored RBCs in humans are leukoreduced. Given the
volume of mouse blood required for leukoreducction, this approach was not considered feasible
in the setting of broad screening of multiple strains. However, we have previously reported
metabolomics analysis of B6 and FVB strains, using filter leukoreduced products.
In this
setting, the same lipid oxidation pathways are associated with poor storage (28). In addition,
dicarboxylic acids remain associated with poor storage in leukoreduced RBCs (data not shown).
13
Thus, while some of the associated change may be due to contaminating leukocytes and/or
platelets, the major findings of lipid peroxidation persist even with leukoreduction. A second
consideration is that a 7 day storage time was chosen for this study, since this allowed the
widest range of differences between strains to be observed, while still allowing for the best
storing strains to have recoveries of greater than 75% (in line with FDA standards for human
RBC storage).
To control for potential differences in recipient phagocytic biology, a single common
recipient strain of mice was used for all donors in the current study. This approach also allowed
an experimental design in which donor RBCs did not have to be manipulated or labeled prior to
transfusion.
However, there is a theoretical risk that one is crossing alloimmune barriers
between strains, which could account for some differences in survival. Naturally occurring RBC
alloantibodies (analogous to ABO in humans) have not been described in mice, and 24 hr
recoveries are typically too short a period of time for adaptive humoral responses to occur; thus,
we did not predict any problems with alloimmunity in the current studies. In support of this
notion, there were no statistically significant differences in 24 hour recoveries of freshly isolated
RBCs, thus indicating that even if alloantibodies were present, they had no clear functional
outcome. Nevertheless, one must give theoretical consideration to possible effects of crossing
strain barriers.
The biological underpinnings that regulate lipid oxidation across strains are unclear;
however alpha-tocopherol and GSH are candidates for being involved in the underlying
processes that leads to lipid peroxidation.
Alpha-tocopherol does have the ability to inhibit
chemical oxidation of RBCs (29); however, the extent to which such is a normal pathway during
RBC storage is unclear and has only been tested in an in vitro setting (30). Of interest, it has
recently been reported that vitamin C and N-acetylcysteine mitigate oxidative stress in in vitro
14
human RBC studies (31). In vivo studies in mice have shown that vitamin C supplementation
can improve storage as measured by 24-hour recoveries (32).
The generation of products of lipid oxidation not only gives insight into underlying RBC
storage biology, but may in of themselves represent a biologically significant component of
transfused RBCs. Among the lipid oxidation products that were observed to both increase with
storage and negatively correlate with RBC recoveries are 5-HETE and the bioactive lipids 9,10DiHOME, and (13-HODE+9-HODE).
In addition, 4-hydroxy-2-nonenal has biological and
signaling properties, in addition to being a common indicator of lipid peroxidation. Interestingly,
in opposition to 5-HETE, 12-HETE had a significant positive correlation to RBC storage. Both 5HETE and 12-HETE are arachidonic acid metabolites generated by separate lipoxygenase
enzymes. Bioactive lipids are known to be involved in complex biologies including inflammation,
coagulation, vascular tone and immunity.
Bioactive lipids have been implicated in the
pathogenesis of transfusion related acute lung injury (TRALI), a potentially lethal sequela of
blood transfusion (33-35). It is also worth considering the source of substrates for lipid oxidation
pathways, such as eicosanoid generation.
Levels of both medium and long chain fatty acids
were strongly correlated with RBC recoveries, and lysolipids and monoacylglycerols increased
with storage, suggesting release of the observed free fatty acids from glycerophospholipid
breakdown. It is unclear if release of free fatty acids from phospholipids precedes lipid oxidation
as a separate step, or is the result of lipid peroxidation, but it is clear that both correlate.
Increases in long chain fatty acids at the time of RBC collection strongly correlated with
the post-storage RBC recovery. Of these, 4 particular long chain fatty acids had a negative
correlation both in fresh RBCs and stored RBCs (palmitate, palmitoleate,10-heptadecenoate,
and cis-vaccenate). There was no significant change in the levels of these 4 long chain fatty
acids between time of collection and after storage.
Although one cannot rule out a
simultaneous increase in production and consumption resulting in an unaltered steady state, a
15
more likely explanation is that increased lipid breakdown (or processes that are associated with
it), as a function of the normal RBC biology, predispose RBCs to poor storage. In contrast to the
above long chain fatty acids, omega-3 fatty acids DPA and DHA had a positive correlation with
24-hr recoveries when measured after storage. EPA can be converted into DPA, which then
can be converted to DHA. EPA was detected in this panel, but had no correlation to RBC
recoveries. There findings are of potential practical value, as they may serve as criteria to
evaluate how RBCs will store through screening at time of donation.
In summary, a model emerges from the current studies in which lipid peroxidation is
associated with poor 24-hour recoveries. Future experimental studies in mice will be required to
test the functional relevance of the tocopherol-ascorbate-GSH axis and lipid peroxidation.
Human studies will also be required to assess the extent to which the observations generated
herein predict human RBC storage biology. The further resolution of these issues is a much
needed step in advancing the ability to predict and control the quality of stored human RBCs.
16
Acknowledgements: We would like to acknowledge the technical and scientific staff at
Metabolon Inc., who carried out the mass spec analysis of the RBC specimens. This work was
supported, in part, by a grant from the National Heart Lung and Blood Institute (HL095479-05).
Conflicts of Interest: JCZ and BloodworksNW have filed intellectual property on the content of
this manuscript. JCZ has a sponsored research agreement with Immucor Inc. and serves on
the scientific advisory board of Rubius Therapeutics, neither of which is associated with the
current studies. None of the other authors have conflicts of interest to declare related to the
current studies.
17
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Lacroix J, Hebert PC, Fergusson DA, et al. Age of transfused blood in critically ill adults. N Engl J
Med. 2015;372(15):1410-1418.
13.
Steiner ME, Ness PM, Assmann SF, et al. Effects of red-cell storage duration on patients
undergoing cardiac surgery. N Engl J Med. 2015;372(15):1419-1429.
14.
Qu L, Triulzi DJ. Clinical effects of red blood cell storage. Cancer control. 2015;22(1):26-37.
15.
Desmarets M, Cadwell CM, Peterson KR, Neades R, Zimring JC. Minor histocompatibility antigens
on transfused leukoreduced units of red blood cells induce bone marrow transplant rejection in a mouse
model. Blood. 2009;114(11):2315-2322.
16.
Gilson CR, Kraus TS, Hod EA, et al. A novel mouse model of red blood cell storage and
posttransfusion in vivo survival. Transfusion. 2009;49(8):1546-1553.
17.
Uchida K. 4-Hydroxy-2-nonenal: a product and mediator of oxidative stress. Prog Lipid Res.
2003;42(4):318-343.
18.
Arun P, Padmakumaran Nair KG, Manojkumar V, Deepadevi KV, Lakshmi LR, Kurup PA.
Decreased hemolysis and lipid peroxidation in blood during storage in the presence of nicotinic acid. Vox
Sang. 1999;76(4):220-225.
19.
Karon BS, van Buskirk CM, Jaben EA, Hoyer JD, Thomas DD. Temporal sequence of major
biochemical events during blood bank storage of packed red blood cells. Blood Transfus.
2012;10(4):453-461.
20.
Knight JA, Searles DA, Blaylock RC. The effect of metal chelators on lipid peroxidation in
irradiated erythrocytes. Ann Clin Lab Sci. 1992;22(6):417-422.
21.
Knight JA, Voorhees RP, Martin L. The effect of metal chelators on lipid peroxidation in stored
erythrocytes. Ann Clin Lab Sci. 1992;22(4):207-213.
22.
Knight JA, Voorhees RP, Martin L, Anstall H. Lipid peroxidation in stored red cells. Transfusion.
1992;32(4):354-357.
19
23.
D'Alessandro A, Blasi B, D'Amici GM, Marrocco C, Zolla L. Red blood cell subpopulations in
freshly drawn blood: application of proteomics and metabolomics to a decades-long biological issue.
Blood Transfus. 2013;11(1):75-87.
24.
D'Alessandro A, Hansen KC, Silliman CC, Moore EE, Kelher M, Banerjee A. Metabolomics of AS-5
RBC supernatants following routine storage. Vox Sang. 2015;108(2):131-140.
25.
D'Alessandro A, Nemkov T, Hansen KC, Szczepiorkowski ZM, Dumont LJ. Red blood cell storage
in additive solution-7 preserves energy and redox metabolism: a metabolomics approach. Transfusion.
2015;55(12):2955-2966.
26.
D'Alessandro A, Nemkov T, Kelher M, et al. Routine storage of red blood cell (RBC) units in
additive solution-3: a comprehensive investigation of the RBC metabolome. Transfusion.
2015;55(6):1155-1168.
27.
Roback JD, Josephson CD, Waller EK, et al. Metabolomics of ADSOL (AS-1) red blood cell storage.
Transfus Med Rev. 2014;28(2):41-55.
28.
Zimring JC, Smith N, Stowell SR, et al. Strain-specific red blood cell storage, metabolism, and
eicosanoid generation in a mouse model. Transfusion. 2014;54(1):137-148.
29.
Claro LM, Leonart MS, Comar SR, do Nascimento AJ. Effect of vitamins C and E on oxidative
processes in human erythrocytes. Cell Biochem Funct. 2006;24(6):531-535.
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Leonart MS, Weffort-Santos AM, Munoz EM, Higuti IH, Fortes VA, Nascimento AJ. Effect of
vitamin E on red blood cell preservation. Braz J Med Biol Res. 1989;22(1):85-86.
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Pallotta V, Gevi F, D'Alessandro A, Zolla L. Storing red blood cells with vitamin C and N-
acetylcysteine prevents oxidative stress-related lesions: a metabolomics overview. Blood Transfus.
2014;12(3):376-387.
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32.
Stowell SR, Smith NH, Zimring JC, et al. Addition of ascorbic acid solution to stored murine red
blood cells increases posttransfusion recovery and decreases microparticles and alloimmunization.
Transfusion. 2013;53(10):2248-2257.
33.
Silliman CC, Moore EE, Kelher MR, Khan SY, Gellar L, Elzi DJ. Identification of lipids that
accumulate during the routine storage of prestorage leukoreduced red blood cells and cause acute lung
injury. Transfusion. 2011;51(12):2549-2554.
34.
Silliman CC, Bjornsen AJ, Wyman TH, et al. Plasma and lipids from stored platelets cause acute
lung injury in an animal model. Transfusion. 2003;43(5):633-640.
35.
Silliman CC, Voelkel NF, Allard JD, et al. Plasma and lipids from stored packed red blood cells
cause acute lung injury in an animal model. J Clin Invest. 1998;101(7):1458-1467.
21
Figure 1: 24 hr Recoveries of Fresh and Stored RBCs across 13 inbred strains of mice. (A)
The phylogenetic distribution of the strains chosen for this study is indicated*.
(B)
Representative flow cytometry plots are shown to indicate the enumeration of fresh tracer and
test RBCs in a pre-transfusion sample (left panel). Recipient GFP+ RBCs are shown, including
empty gates where fresh tracer and test RBCs appear (middle panel). The final mixture in a
recipient mouse, 24 hours after transfusion, is shown (right panel). (C) Individual results of
three out of three experiments of stored RBCs is shown. (D) Individual results of three out of
three experiments of fresh RBCs is shown [KK/HIJ, LG/J, and C3H/HeJ only had replicates of
fresh RBCs]. * Figure 1A is reproduced from Genome Res 2004:14:1806-11 with kind
permission of Dr. Petkov and Genome Research
Figure 2: Principal Component Analysis of Metabolites Measured in Fresh and Stored RBCs.
PCA for the indicated strains (based on color) are shown for both fresh (spheres) and stored
(cylinders) RBCs.
Figure 3: Products of Glycolysis are Common Across Strains and Do not Correlate with 24 hour
Recoveries. (A) Glucose levels were equivalent in fresh RBCs from each strain and decreased
commonly after storage. (B) 2,3-DPG was equivalent across strains and uniformly decreased
after 7 days of storage.
(C) Lactate was uniformly low in fresh RBCs and increased
equivalently, over storage, for all strains analyzed. Open boxes represent levels at time of
collection whereas grey boxes indicate levels after storage.
All levels of metabolites are
relative concentrations based upon areas under the peaks and are averages for all three
experiments shown in figure 1.
Figure 4: Levels of the indicated metabolite are shown in fresh (white) and stored (gray)
samples, as are the correlations of the metabolite with 24 hour RBC recoveries. (A+B) DPA,
22
(C+D) DHA, (E+F) dodecanedioate, (G+H) 16-hydroxypalmitate, (I+J) 5-HETE, (K+L) 12-HETE.
Correlations of levels of aspartate (M) and palmitate (N) in freshly isolated RBCs are shown vs.
the 24 hr RBC recoveries after 7 days of storage. Open boxes represent levels at time of
collection whereas grey boxes indicate levels after storage. Correlation calculations represent
Pearson’s coefficient. All levels of metabolites are relative concentrations based upon areas
under the peaks and are averages for all three experiments shown in figure 1. Correlation plots
show combined data from all three of the indicated experiments in figure 1.
Figure 5: Anti-oxidant pathways during RBC storage. Levels of alpha-tocopherol in freshly
collected RBCs and after storage are shown (A).
Correlation plots are shown for alpha-
tocopherol for levels in fresh, stored, and the ration of fresh/stored (F). Levels of GSH in
freshly collected RBCs and after storage are shown (B). Correlation plots are shown for GSH
for levels in fresh, stored, and the ration of fresh/stored (G). Levels of GSSG (C), 4-hydroxynonenal-glutathione (D), and ascorbate (E) are shown in freshly collected RBCs and after
storage. Correlations between the ratio of N-acetylcysteine (fold change) is shown (H). Open
boxes represent levels at time of collection whereas grey boxes indicate levels after storage.
Correlation calculations represent Pearson’s coefficient. All levels of metabolites are relative
concentrations based upon areas under the peaks and are averages for all three experiments
shown in figure 1. All horizontal axes labeled 24-hour recovery represent RBCs circulating 24hours post-transfusion, as described in methods. Correlation plots show combined data from all
three of the indicated experiments in figure 1.
23
Supplemental Table 1
Tukey's multiple comp
C57Bl/6J vs. FVB/NJ
C57Bl/6J vs. Balb/cByj
C57Bl/6J vs. BTBR T+Itpr3tf/J
C57Bl/6J vs. 129S1/SvmJ
C57Bl/6J vs. 129X1/SvJ
C57Bl/6J vs. A/J
C57Bl/6J vs. AKR/J
C57Bl/6J vs. C3H/HeJ
C57Bl/6J vs. DBA/2j
C57Bl/6J vs. NOD/ShiLtJ
C57Bl/6J vs. KK/HiJ
C57Bl/6J vs. LG/J
FVB/NJ vs. Balb/cByj
FVB/NJ vs. BTBR T+Itpr3tf/J
FVB/NJ vs. 129S1/SvmJ
FVB/NJ vs. 129X1/SvJ
FVB/NJ vs. A/J
FVB/NJ vs. AKR/J
FVB/NJ vs. C3H/HeJ
FVB/NJ vs. DBA/2j
FVB/NJ vs. NOD/ShiLtJ
FVB/NJ vs. KK/HiJ
FVB/NJ vs. LG/J
Balb/cByj vs. BTBR T+Itpr3tf/J
Balb/cByj vs. 129S1/SvmJ
Balb/cByj vs. 129X1/SvJ
Balb/cByj vs. A/J
Balb/cByj vs. AKR/J
Balb/cByj vs. C3H/HeJ
Balb/cByj vs. DBA/2j
Balb/cByj vs. NOD/ShiLtJ
Balb/cByj vs. KK/HiJ
Balb/cByj vs. LG/J
BTBR T+Itpr3tf/J vs. 129S1/SvmJ
BTBR T+Itpr3tf/J vs. 129X1/SvJ
BTBR T+Itpr3tf/J vs. A/J
BTBR T+Itpr3tf/J vs. AKR/J
BTBR T+Itpr3tf/J vs. C3H/HeJ
BTBR T+Itpr3tf/J vs. DBA/2j
BTBR T+Itpr3tf/J vs. NOD/ShiLtJ
BTBR T+Itpr3tf/J vs. KK/HiJ
BTBR T+Itpr3tf/J vs. LG/J
129S1/SvmJ vs. 129X1/SvJ
129S1/SvmJ vs. A/J
129S1/SvmJ vs. AKR/J
129S1/SvmJ vs. C3H/HeJ
129S1/SvmJ vs. DBA/2j
129S1/SvmJ vs. NOD/ShiLtJ
129S1/SvmJ vs. KK/HiJ
129S1/SvmJ vs. LG/J
129X1/SvJ vs. A/J
129X1/SvJ vs. AKR/J
129X1/SvJ vs. C3H/HeJ
129X1/SvJ vs. DBA/2j
129X1/SvJ vs. NOD/ShiLtJ
129X1/SvJ vs. KK/HiJ
129X1/SvJ vs. LG/J
A/J vs. AKR/J
A/J vs. C3H/HeJ
A/J vs. DBA/2j
A/J vs. NOD/ShiLtJ
A/J vs. KK/HiJ
A/J vs. LG/J
AKR/J vs. C3H/HeJ
AKR/J vs. DBA/2j
AKR/J vs. NOD/ShiLtJ
AKR/J vs. KK/HiJ
AKR/J vs. LG/J
C3H/HeJ vs. DBA/2j
C3H/HeJ vs. NOD/ShiLtJ
C3H/HeJ vs. KK/HiJ
C3H/HeJ vs. LG/J
DBA/2j vs. NOD/ShiLtJ
DBA/2j vs. KK/HiJ
DBA/2j vs. LG/J
NOD/ShiLtJ vs. KK/HiJ
NOD/ShiLtJ vs. LG/J
KK/HiJ vs. LG/J
Mean Diff.
-0.05167
-0.01967
-0.07567
0.01733
-0.04333
-0.024
0.05933
-0.03717
0.03867
0.03
0.3937
0.1167
0.032
-0.024
0.069
0.008333
0.02767
0.111
0.0145
0.09033
0.08167
0.4453
0.1683
-0.056
0.037
-0.02367
-0.004333
0.079
-0.0175
0.05833
0.04967
0.4133
0.1363
0.093
0.03233
0.05167
0.135
0.0385
0.1143
0.1057
0.4693
0.1923
-0.06067
-0.04133
0.042
-0.0545
0.02133
0.01267
0.3763
0.09933
0.01933
0.1027
0.006167
0.082
0.07333
0.437
0.16
0.08333
-0.01317
0.06267
0.054
0.4177
0.1407
-0.0965
-0.02067
-0.02933
0.3343
0.05733
0.07583
0.06717
0.4308
0.1538
-0.008667
0.355
0.078
0.3637
0.08667
-0.277
Fresh RBC recovery
95% CI of diff.
Result
-0.7702 to 0.6668
ns
-0.7382 to 0.6988
ns
-0.7942 to 0.6428
ns
-0.7012 to 0.7358
ns
-0.7618 to 0.6752
ns
-0.7425 to 0.6945
ns
-0.6592 to 0.7778
ns
-0.8405 to 0.7661
ns
-0.6798 to 0.7572
ns
-0.6885 to 0.7485
ns
-0.3248 to 1.112
ns
-0.6018 to 0.8352
ns
-0.6865 to 0.7505
ns
-0.7425 to 0.6945
ns
-0.6495 to 0.7875
ns
-0.7102 to 0.7268
ns
-0.6908 to 0.7462
ns
-0.6075 to 0.8295
ns
-0.7888 to 0.8178
ns
-0.6282 to 0.8088
ns
-0.6368 to 0.8002
ns
-0.2732 to 1.164
ns
-0.5502 to 0.8868
ns
-0.7745 to 0.6625
ns
-0.6815 to 0.7555
ns
-0.7422 to 0.6948
ns
-0.7228 to 0.7142
ns
-0.6395 to 0.7975
ns
-0.8208 to 0.7858
ns
-0.6602 to 0.7768
ns
-0.6688 to 0.7682
ns
-0.3052 to 1.132
ns
-0.5822 to 0.8548
ns
-0.6255 to 0.8115
ns
-0.6862 to 0.7508
ns
-0.6668 to 0.7702
ns
-0.5835 to 0.8535
ns
-0.7648 to 0.8418
ns
-0.6042 to 0.8328
ns
-0.6128 to 0.8242
ns
-0.2492 to 1.188
ns
-0.5262 to 0.9108
ns
-0.7792 to 0.6578
ns
-0.7598 to 0.6772
ns
-0.6765 to 0.7605
ns
-0.8578 to 0.7488
ns
-0.6972 to 0.7398
ns
-0.7058 to 0.7312
ns
-0.3422 to 1.095
ns
-0.6192 to 0.8178
ns
-0.6992 to 0.7378
ns
-0.6158 to 0.8212
ns
-0.7971 to 0.8095
ns
-0.6365 to 0.8005
ns
-0.6452 to 0.7918
ns
-0.2815 to 1.156
ns
-0.5585 to 0.8785
ns
-0.6352 to 0.8018
ns
-0.8165 to 0.7901
ns
-0.6558 to 0.7812
ns
-0.6645 to 0.7725
ns
-0.3008 to 1.136
ns
-0.5778 to 0.8592
ns
-0.8998 to 0.7068
ns
-0.7392 to 0.6978
ns
-0.7478 to 0.6892
ns
-0.3842 to 1.053
ns
-0.6612 to 0.7758
ns
-0.7275 to 0.8791
ns
-0.7361 to 0.8705
ns
-0.3725 to 1.234
ns
-0.6495 to 0.9571
ns
-0.7272 to 0.7098
ns
-0.3635 to 1.074
ns
-0.6405 to 0.7965
ns
-0.3548 to 1.082
ns
-0.6318 to 0.8052
ns
-0.9955 to 0.4415
ns
Adj P Value
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.7247
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.5613
0.9995
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.6639
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.4852
0.9982
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.7751
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.5882
0.9997
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.6502
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.878
> 0.9999
> 0.9999
> 0.9999
0.7493
> 0.9999
> 0.9999
0.8312
> 0.9999
0.8093
> 0.9999
0.9633
Mean Diff.
0.6696
0.05882
0.01742
0.2859
0.2967
0.2176
0.7143
0.5136
0.4519
0.3601
1.281
0.9553
-0.6107
-0.6521
-0.3837
-0.3729
-0.452
0.04473
-0.1559
-0.2177
-0.3095
0.6111
0.2858
-0.04139
0.227
0.2378
0.1588
0.6555
0.4548
0.3931
0.3012
1.222
0.8965
0.2684
0.2792
0.2002
0.6969
0.4962
0.4345
0.3426
1.263
0.9379
0.01079
-0.06828
0.4284
0.2278
0.166
0.0742
0.9948
0.6695
-0.07907
0.4176
0.217
0.1552
0.06341
0.984
0.6587
0.4967
0.2961
0.2343
0.1425
1.063
0.7378
-0.2006
-0.2624
-0.3542
0.5664
0.241
-0.06176
-0.1536
0.767
0.4417
-0.09182
0.8288
0.5034
0.9206
0.5953
-0.3253
Stored RBC recovery
95% CI of diff.
Result
0.1391 to 1.200
**
-0.4716 to 0.5892
ns
-0.5130 to 0.5478
ns
-0.2446 to 0.8163
ns
-0.2338 to 0.8271
ns
-0.3128 to 0.7480
ns
0.1839 to 1.245
**
-0.01678 to 1.044
ns
-0.07854 to 0.9823
ns
-0.1704 to 0.8905
ns
0.7502 to 1.811
****
0.4249 to 1.486
****
-1.141 to -0.08032
*
-1.183 to -0.1217
**
-0.9141 to 0.1467
ns
-0.9033 to 0.1575
ns
-0.9824 to 0.07844
ns
-0.4857 to 0.5752
ns
-0.6863 to 0.3745
ns
-0.7481 to 0.3127
ns
-0.8399 to 0.2209
ns
0.08067 to 1.142
*
-0.2447 to 0.8162
ns
-0.5718 to 0.4890
ns
-0.3034 to 0.7575
ns
-0.2926 to 0.7683
ns
-0.3717 to 0.6892
ns
0.1250 to 1.186
**
-0.07560 to 0.9853
ns
-0.1374 to 0.9235
ns
-0.2292 to 0.8317
ns
0.6914 to 1.752
****
0.3661 to 1.427
***
-0.2620 to 0.7989
ns
-0.2512 to 0.8097
ns
-0.3303 to 0.7306
ns
0.1664 to 1.227
**
-0.03420 to 1.027
ns
-0.09596 to 0.9649
ns
-0.1878 to 0.8731
ns
0.7328 to 1.794
****
0.4075 to 1.468
****
-0.5196 to 0.5412
ns
-0.5987 to 0.4621
ns
-0.1020 to 0.9589
ns
-0.3026 to 0.7582
ns
-0.3644 to 0.6964
ns
-0.4562 to 0.6046
ns
0.4644 to 1.525
****
0.1390 to 1.200
**
-0.6095 to 0.4514
ns
-0.1128 to 0.9481
ns
-0.3134 to 0.7474
ns
-0.3752 to 0.6857
ns
-0.4670 to 0.5938
ns
0.4536 to 1.514
****
0.1283 to 1.189
**
-0.03372 to 1.027
ns
-0.2344 to 0.8265
ns
-0.2961 to 0.7647
ns
-0.3879 to 0.6729
ns
0.5327 to 1.594
****
0.2073 to 1.268
**
-0.7311 to 0.3298
ns
-0.7928 to 0.2680
ns
-0.8846 to 0.1762
ns
0.03595 to 1.097
*
-0.2894 to 0.7715
ns
-0.5922 to 0.4687
ns
-0.6840 to 0.3768
ns
0.2366 to 1.297
***
-0.08874 to 0.9721
ns
-0.6222 to 0.4386
ns
0.2984 to 1.359
***
-0.02698 to 1.034
ns
0.3902 to 1.451
****
0.06484 to 1.126
*
-0.8558 to 0.2051
ns
Adj P Value
0.0053
> 0.9999
> 0.9999
0.7483
0.7045
0.9457
0.0025
0.0643
0.1525
0.4332
< 0.0001
< 0.0001
0.014
0.0071
0.3426
0.3826
0.1524
> 0.9999
0.996
0.9455
0.65
0.014
0.7487
> 0.9999
0.9282
0.9043
0.9953
0.0067
0.1468
0.31
0.6853
< 0.0001
0.0001
0.8134
0.774
0.9697
0.0033
0.0829
0.1907
0.506
< 0.0001
< 0.0001
> 0.9999
> 0.9999
0.2056
0.9268
0.9931
> 0.9999
< 0.0001
0.0053
> 0.9999
0.2343
0.9467
0.9961
> 0.9999
< 0.0001
0.0063
0.0823
0.707
0.9126
0.9982
< 0.0001
0.0016
0.9692
0.8339
0.4572
0.0287
0.8964
> 0.9999
0.9965
0.001
0.1741
> 0.9999
0.0003
0.0746
< 0.0001
0.0181
0.5811
Supplemental Table 2
Stored RBCs
Positive Correlation
docosapentaenoate (n6 DPA; 22:5n6)
cis-4-decenoyl carnitine
1-arachidonoyl-GPI (20:4)*
docosahexaenoate (DHA; 22:6n3)
palmitoyl-oleoyl-glycerophosphoglycerol (2)
1-arachidonoyl-GPE (20:4)*
17-HDoHe
1-linoleoylglycerol (18:2)
p-value
q-value
CORRELATION
2.87E-06
6.41E-06
2.75E-05
4.08E-05
4.19E-05
1.00E-04
1.00E-04
1.00E-04
2.83E-05
6.08E-05
2.00E-04
3.00E-04
3.00E-04
6.00E-04
6.00E-04
6.00E-04
6.52E-01
6.35E-01
5.99E-01
5.89E-01
5.88E-01
5.62E-01
5.55E-01
5.53E-01
alpha-tocopherol
2.00E-04
1.10E-03
5.39E-01
12-HETE
tryptophan
Negative Correlation
dodecanedioate
16-hydroxypalmitate
5-hydroxyhexanoate
sebacate (decanedioate)
2-hydroxydecanoate
2-aminoheptanoate
caproate (6:0)
heptanoate (7:0)
caprylate (8:0)
2-hydroxyoctanoate
undecanedioate
pelargonate (9:0)
13-HODE + 9-HODE
9,10-DiHOME
8-hydroxyoctanoate
pentadecanoate (15:0)
azelate (nonanedioate)
alpha-hydroxycaproate
hexadecanedioate
suberate (octanedioate)
3-hydroxysebacate
2-hydroxypalmitate
4-hydroxy-nonenal-glutathione
indole-3-carboxylic acid
pimelate (heptanedioate)
4-hydroxybutyrate (GHB)
glutarate (pentanedioate)
5-HETE
palmitoleate (16:1n7)
phenylalanylglycine
2-oxoadipate
2-hydroxyadipate
4-methyl-2-oxopentanoate
tetradecanedioate
1-palmitoylglycerol (16:0)
xanthine
cis-vaccenate (18:1n7)
caprate (10:0)
arachidate (20:0)
myristate (14:0)
methionine sulfoxide
palmitate (16:0)
glycerol 3-phosphate
1-oleoyl-GPI (18:1)*
1-palmitoyl-GPI (16:0)*
6-oxopiperidine-2-carboxylic acid
10-heptadecenoate (17:1n7)
3-methyl-2-oxobutyrate
4-hydroxy-2-nonenal
3.00E-04
5.00E-04
1.50E-03
2.30E-03
1.80E-14
8.40E-14
1.17E-13
1.71E-12
2.39E-12
5.55E-12
1.01E-10
1.18E-10
1.28E-10
1.89E-10
1.99E-10
5.51E-10
1.65E-09
4.60E-09
1.33E-08
6.51E-08
7.31E-08
9.40E-08
1.18E-07
1.58E-07
1.63E-07
5.99E-07
6.64E-07
8.70E-07
9.77E-07
8.34E-06
1.23E-05
1.60E-05
1.89E-05
2.05E-05
4.15E-05
4.18E-05
1.00E-04
1.00E-04
2.00E-04
2.00E-04
2.00E-04
2.00E-04
3.00E-04
3.00E-04
4.00E-04
4.00E-04
5.00E-04
5.00E-04
5.00E-04
6.00E-04
6.00E-04
7.00E-04
7.00E-04
Fresh RBCs
Positive Correlation
aspartate
2'-deoxyuridine
deoxycarnitine
glycylleucine
trans-4-hydroxyproline
thymidine
isoleucylglycine
gamma-glutamyltyrosine
valylglycine
N6-acetyllysine
glutamine
N-acetyltaurine
N-acetylglycine
5,6-dihydrothymine
Negative Correlation
palmitate (16:0)
Super Pathway
Sub Pathway
Polyunsaturated Fatty Acid (n3 and n6)
Fatty Acid Metabolism(Acyl Carnitine)
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
Phosphatidylglycerol
Lysolipid
Fatty Acid, Monohydroxy
Monoacylglycerol
5.35E-01
5.12E-01
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Cofactors and
Vitamins
Lipid
Amino Acid
4.72E-12
9.99E-12
9.99E-12
1.10E-10
1.22E-10
2.37E-10
3.64E-09
3.64E-09
3.64E-09
4.64E-09
4.64E-09
1.18E-08
3.25E-08
8.42E-08
2.27E-07
1.04E-06
1.10E-06
1.34E-06
1.59E-06
1.99E-06
1.99E-06
6.98E-06
7.40E-06
9.29E-06
1.00E-05
7.63E-05
1.00E-04
1.00E-04
2.00E-04
2.00E-04
3.00E-04
3.00E-04
6.00E-04
6.00E-04
1.10E-03
1.10E-03
1.10E-03
1.10E-03
1.50E-03
1.50E-03
2.00E-03
2.00E-03
2.30E-03
2.30E-03
2.30E-03
2.70E-03
2.70E-03
3.00E-03
3.00E-03
-8.79E-01
-8.69E-01
-8.67E-01
-8.46E-01
-8.43E-01
-8.36E-01
-8.08E-01
-8.06E-01
-8.05E-01
-8.01E-01
-8.01E-01
-7.89E-01
-7.75E-01
-7.62E-01
-7.47E-01
-7.23E-01
-7.21E-01
-7.17E-01
-7.13E-01
-7.08E-01
-7.07E-01
-6.84E-01
-6.82E-01
-6.77E-01
-6.74E-01
-6.28E-01
-6.19E-01
-6.13E-01
-6.09E-01
-6.07E-01
-5.89E-01
-5.88E-01
-5.63E-01
-5.55E-01
-5.51E-01
-5.50E-01
-5.39E-01
-5.39E-01
-5.32E-01
-5.29E-01
-5.24E-01
-5.18E-01
-5.16E-01
-5.16E-01
-5.16E-01
-5.09E-01
-5.08E-01
-5.02E-01
-5.02E-01
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Amino Acid
Amino Acid
Lipid
Lipid
Amino Acid
Lipid
Lipid
Peptide
Amino Acid
Lipid
Amino Acid
Lipid
Lipid
Nucleotide
Lipid
Lipid
Lipid
Lipid
Amino Acid
Lipid
Lipid
Lipid
Lipid
Amino Acid
Lipid
Amino Acid
Lipid
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Amino
Medium Chain Fatty Acid
Medium Chain Fatty Acid
Medium Chain Fatty Acid
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Medium Chain Fatty Acid
Fatty Acid, Monohydroxy
Fatty Acid, Dihydroxy
Fatty Acid, Monohydroxy
Long Chain Fatty Acid
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Monohydroxy
Glutathione Metabolism
Tryptophan Metabolism
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Lysine Metabolism
Eicosanoid
Long Chain Fatty Acid
Dipeptide
Lysine Metabolism
Fatty Acid, Dicarboxylate
Leucine, Isoleucine and Valine Metabolism
Fatty Acid, Dicarboxylate
Monoacylglycerol
Purine Metabolism, (Hypo)Xanthine/Inosine containing
Long Chain Fatty Acid
Medium Chain Fatty Acid
Long Chain Fatty Acid
Long Chain Fatty Acid
Methionine, Cysteine, SAM and Taurine Metabolism
Long Chain Fatty Acid
Glycerolipid Metabolism
Lysolipid
Lysolipid
Lysine Metabolism
Long Chain Fatty Acid
Leucine, Isoleucine and Valine Metabolism
Fatty Acid, Oxidized
p-value
q-value
CORRELATION
1.11E-06
9.78E-06
2.00E-04
3.00E-04
4.00E-04
4.00E-04
5.00E-04
6.00E-04
7.00E-04
9.00E-04
9.00E-04
9.00E-04
1.20E-03
1.30E-03
3.00E-04
9.00E-04
4.00E-03
4.90E-03
5.30E-03
5.30E-03
5.80E-03
6.40E-03
7.20E-03
7.60E-03
7.60E-03
7.60E-03
9.30E-03
9.50E-03
7.12E-01
6.65E-01
5.81E-01
5.67E-01
5.59E-01
5.56E-01
5.51E-01
5.44E-01
5.41E-01
5.31E-01
5.31E-01
5.29E-01
5.19E-01
5.15E-01
7.22E-06
9.00E-04
-0.67
Tocopherol Metabolism
Eicosanoid
Tryptophan Metabolism
Super Pathway
Sub Pathway
Amino Acid
Nucleotide
Lipid
Peptide
Amino Acid
Nucleotide
Peptide
Peptide
Peptide
Amino Acid
Amino Acid
Amino Acid
Amino Acid
Nucleotide
Alanine and Aspartate Metabolism
Pyrimidine Metabolism, Uracil Containing
Carnitine Metabolism
Dipeptide
Urea cycle; Arginine and Proline Metabolism
Pyrimidine Metabolism, Thymine containing
Dipeptide
Gamma-glutamyl Amino Acid
Dipeptide
Lysine Metabolism
Glutamate Metabolism
Methionine, Cysteine, SAM and Taurine Metabolism
Glycine, Serine and Threonine Metabolism
Pyrimidine Metabolism, Thymine containing
Lipid
Long Chain Fatty Acid
Supplemental Table 2
glycerol 3-phosphate
alpha-ketoglutarate
palmitoleate (16:1n7)
stearate (18:0)
1-oleoylglycerol (18:1)
linoleate (18:2n6)
eicosenoate (20:1)
10-heptadecenoate (17:1n7)
dihomo-linoleate (20:2n6)
alpha-tocopherol
4-hydroxy-nonenal-glutathione
20a-dihydroprogesterone
margarate (17:0)
4-methyl-2-oxopentanoate
2-phosphoglycerate
oleate (18:1n9)
linolenate [alpha or gamma; (18:3n3 or 6)]
3-methyl-2-oxobutyrate
cis-vaccenate (18:1n7)
10-nonadecenoate (19:1n9)
succinylcarnitine
3-methyl-2-oxovalerate
2-oleoylglycerol (18:1)
1.40E-05
2.47E-05
7.92E-05
9.83E-05
1.00E-04
1.00E-04
1.00E-04
2.00E-04
2.00E-04
2.00E-04
3.00E-04
3.00E-04
4.00E-04
4.00E-04
5.00E-04
5.00E-04
6.00E-04
8.00E-04
8.00E-04
9.00E-04
1.10E-03
1.10E-03
1.30E-03
1.00E-03
1.40E-03
2.80E-03
2.80E-03
2.80E-03
2.80E-03
2.80E-03
4.00E-03
4.00E-03
4.00E-03
4.90E-03
4.90E-03
5.30E-03
5.30E-03
5.80E-03
5.80E-03
6.40E-03
7.60E-03
7.60E-03
7.60E-03
8.80E-03
8.80E-03
9.50E-03
-0.66
-0.64
-0.61
-0.60
-0.60
-0.60
-0.59
-0.59
-0.58
-0.58
-0.57
-0.56
-0.56
-0.56
-0.55
-0.55
-0.55
-0.53
-0.53
-0.53
-0.52
-0.52
-0.52
Lipid
Energy
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Vitamin
Amino Acid
Lipid
Lipid
Amino Acid
Carbohydrate
Lipid
Lipid
Amino Acid
Lipid
Lipid
Energy
Amino Acid
Lipid
Glycerolipid Metabolism
TCA Cycle
Long Chain Fatty Acid
Long Chain Fatty Acid
Monoacylglycerol
Polyunsaturated Fatty Acid (n3 and n6)
Long Chain Fatty Acid
Long Chain Fatty Acid
Polyunsaturated Fatty Acid (n3 and n6)
Tocopherol
Glutathione Metabolism
Steroid
Long Chain Fatty Acid
Leucine, Isoleucine and Valine Metabolism
Glycolysis, Gluconeogenesis, and Pyruvate Metabolism
Long Chain Fatty Acid
Polyunsaturated Fatty Acid (n3 and n6)
Leucine, Isoleucine and Valine Metabolism
Long Chain Fatty Acid
Long Chain Fatty Acid
TCA Cycle
Leucine, Isoleucine and Valine Metabolism
Monoacylglycerol
Ratio of Stored to Fresh
Positive Correlation
1-arachidonoyl-GPI (20:4)*
dihomo-linolenate (20:3n3 or n6)
1-linoleoylglycerol (18:2)
12-HETE
alpha-tocopherol
1-arachidonoyl-GPE (20:4)*
docosahexaenoate (DHA; 22:6n3)
glutathione, reduced (GSH)
adrenate (22:4n6)
1-linoleoyl-GPE (18:2)*
docosapentaenoate (n6 DPA; 22:5n6)
docosapentaenoate (n3 DPA; 22:5n3)
17-HDoHe
1-linoleoyl-GPI (18:2)*
cis-4-decenoyl carnitine
stearoyl-arachidonoyl-glycerophosphocholine(2)
2-oleoylglycerol (18:1)
p-value
q-value
CORRELATION
Super Pathway
Sub Pathway
4.17E-06
5.49E-06
6.43E-06
1.41E-05
1.41E-05
1.83E-05
3.34E-05
6.88E-05
7.83E-05
2.00E-04
3.00E-04
5.00E-04
5.00E-04
6.00E-04
8.00E-04
1.20E-03
1.20E-03
5.35E-05
6.52E-05
6.95E-05
1.00E-04
1.00E-04
2.00E-04
3.00E-04
5.00E-04
6.00E-04
1.30E-03
1.90E-03
2.90E-03
2.90E-03
3.20E-03
4.20E-03
5.70E-03
5.70E-03
6.77E-01
6.71E-01
6.67E-01
6.49E-01
6.49E-01
6.42E-01
6.27E-01
6.07E-01
6.03E-01
5.79E-01
5.65E-01
5.48E-01
5.47E-01
5.36E-01
5.28E-01
5.13E-01
5.11E-01
lipid
lipid
lipid
lipid
Vitamin
lipid
lipid
Amino Acid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
Lysolipid
Eicosanoid
Tocopherol
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
glutathione metabolism
Polyunsaturated Fatty Acid (n3 and n6)
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
Polyunsaturated Fatty Acid (n3 and n6)
Fatty Acid, Monohydroxy
Lysolipid
Fatty Acid Metabolism (Acyl Carnitines)
Phosphatidylcholine Metabolism
monoacylglycerol
Negative Correlation
undecanedioate
sebacate (decanedioate)
5-hydroxyhexanoate
2-aminoheptanoate
2-hydroxydecanoate
azelate (nonanedioate)
suberate (octanedioate)
2-hydroxyoctanoate
caprylate (8:0)
heptanoate (7:0)
8-hydroxyoctanoate
16-hydroxypalmitate
kynurenine
indole-3-carboxylic acid
2-hydroxypalmitate
N6-succinyladenosine
glutarate (pentanedioate)
pelargonate (9:0)
pimelate (heptanedioate)
hexadecanedioate
dodecanedioate
3-hydroxysebacate
caproate (6:0)
glycolate (hydroxyacetate)
4-hydroxy-nonenal-glutathione
N6-acetyllysine
2-hydroxystearate
9,10-DiHOME
alpha-hydroxycaproate
glycylvaline
2-hydroxybutyrate (AHB)
aspartate
uracil
1.15E-10
5.01E-10
1.90E-09
2.67E-09
3.18E-09
1.96E-08
2.48E-08
2.76E-08
4.19E-08
9.66E-08
2.23E-07
2.98E-07
3.71E-07
1.05E-06
1.29E-06
1.87E-06
2.82E-06
4.28E-06
6.29E-06
2.23E-05
2.45E-05
4.49E-05
6.96E-05
7.31E-05
1.00E-04
1.00E-04
3.00E-04
5.00E-04
6.00E-04
6.00E-04
1.00E-03
1.00E-03
1.00E-03
2.73E-08
5.95E-08
1.51E-07
1.51E-07
1.51E-07
7.76E-07
8.20E-07
8.20E-07
1.11E-06
2.30E-06
4.82E-06
5.90E-06
6.78E-06
1.78E-05
2.04E-05
2.78E-05
3.94E-05
5.35E-05
6.95E-05
2.00E-04
2.00E-04
4.00E-04
5.00E-04
5.00E-04
7.00E-04
7.00E-04
1.90E-03
2.90E-03
3.20E-03
3.20E-03
5.00E-03
5.00E-03
5.00E-03
-8.36E-01
-8.21E-01
-8.05E-01
-8.01E-01
-7.99E-01
-7.74E-01
-7.70E-01
-7.69E-01
-7.62E-01
-7.49E-01
-7.35E-01
-7.30E-01
-7.26E-01
-7.06E-01
-7.02E-01
-6.94E-01
-6.86E-01
-6.77E-01
-6.68E-01
-6.37E-01
-6.35E-01
-6.19E-01
-6.06E-01
-6.05E-01
-5.93E-01
-5.87E-01
-5.58E-01
-5.44E-01
-5.39E-01
-5.36E-01
-5.21E-01
-5.20E-01
-5.17E-01
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
amino acid
amino acid
lipid
nucleotide
amino acid
lipid
lipid
lipid
lipid
lipid
lipid
Xenobiotic
amino acid
amino acid
lipid
lipid
lipid
peptide
amino acid
amino acid
nucleotide
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Amino
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Medium Chain Fatty Acid
Medium Chain Fatty Acid
Fatty Acid, Monohydroxy
Fatty Acid, Monohydroxy
Tryptophan Metabolism
Tryptophan Metabolism
Fatty Acid, Monohydroxy
Purine Metabolism
Lysine Metabolism
Medium Chain Fatty Acid
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Medium Chain Fatty Acid
Chemical
Glutathione Metabolism
Lysine Metabolism
Fatty Acid, Monohydroxy
Fatty Acid, Dihyrdoxy
Fatty Acid, Monohydroxy
dipeptide
Methionine, Cysteine, SAM and Taurine Metabolism
Alanine and Aspartate Metabolism
Pyrimidine Metabolism, Uracil containing
Supplemental Table 1: ANOVA analysis of statistical significance in differences of 24 hr RBC
recoveries between strains for fresh or stored RBCs.
Recoveries of stored RBCs were
compared for differences in mean of log10-transformed data.
No significant differences were
observed for any fresh RBCs. Significant differences for stored RBCs are indicated by shading.
All values show combined data of all three experiments shown in figure 1.
Supplemental Table 2: All analytes that correlated with 24 hr RBC recoveries of stored RBCs
that have a Pearson’s coefficient of greater than 0.5 or lesser than -0.5, and also had p values
of less than 0.05 and q values of less than 0.01 are shown. Lists are broken down as to
“positive correlations” and “negative correlations” of the indicated analytes with 24-hour
recoveries of transfused stored RBCs with regards to analytes measured in (Stored RBCs),
(Fresh RBCs), or the (Ratio of Stored to Fresh RBCs). All correlations were performed with 24hour recoveries of stored RBCs. Thus, the correlations for (Fresh RBCs) are the levels of
measured analytes at time of collection correlated to the 24 hour recoveries obtained 7 days
later after storage. All values show combined data of all three experiments shown in figure 1.
Supplemental Methods
Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS):
The
LC/MS
platform
was
based
on
a
Waters
ACQUITY
ultra-performance
liquid
chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass
spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap
mass analyzer operated at 35,000 mass resolution.
The sample extract was dried then
reconstituted in acidic or basic LC-compatible solvents, each of which contained 8 or more
injection standards at fixed concentrations to ensure injection and chromatographic consistency.
One aliquot was analyzed using acidic positive ion optimized conditions and the other using
basic negative ion optimized conditions in two independent injections using separate dedicated
columns (Waters UPLC BEH C18-2.1x100 mm, 1.7 µm).
Extracts reconstituted in acidic
conditions were gradient eluted from a C18 column using water and methanol containing 0.1%
formic acid. The basic extracts were similarly eluted from C18 using methanol and water,
however with 6.5mM Ammonium Bicarbonate. The third aliquot was analyzed via negative
ionization following elution from a HILIC column (Waters UPLC BEH Amide 2.1x150 mm, 1.7
µm) using a gradient consisting of water and acetonitrile with 10mM Ammonium Formate. The
MS analysis alternated between MS and data-dependent MS2 scans using dynamic exclusion,
and the scan range was from 80-1000 m/z.
Gas Chromatography-Mass Spectroscopy (GC-MS): The samples destined for analysis by GCMS were dried under vacuum for a minimum of 18 h prior to being derivatized under dried
nitrogen using bistrimethyl-silyltrifluoroacetamide. Derivatized samples were separated on a 5%
diphenyl / 95% dimethyl polysiloxane fused silica column (20 m x 0.18 mm ID; 0.18 um film
thickness) with helium as carrier gas and a temperature ramp from 60° to 340°C in a 17.5 min
period. Samples were analyzed on a Thermo-Finnigan Trace DSQ fast-scanning single-
quadrupole mass spectrometer using electron impact ionization (EI) and operated at unit mass
resolving power. The scan range was from 50–750 m/z.
Supplemental Table 1
Tukey's multiple comp
C57Bl/6J vs. FVB/NJ
C57Bl/6J vs. Balb/cByj
C57Bl/6J vs. BTBR T+Itpr3tf/J
C57Bl/6J vs. 129S1/SvmJ
C57Bl/6J vs. 129X1/SvJ
C57Bl/6J vs. A/J
C57Bl/6J vs. AKR/J
C57Bl/6J vs. C3H/HeJ
C57Bl/6J vs. DBA/2j
C57Bl/6J vs. NOD/ShiLtJ
C57Bl/6J vs. KK/HiJ
C57Bl/6J vs. LG/J
FVB/NJ vs. Balb/cByj
FVB/NJ vs. BTBR T+Itpr3tf/J
FVB/NJ vs. 129S1/SvmJ
FVB/NJ vs. 129X1/SvJ
FVB/NJ vs. A/J
FVB/NJ vs. AKR/J
FVB/NJ vs. C3H/HeJ
FVB/NJ vs. DBA/2j
FVB/NJ vs. NOD/ShiLtJ
FVB/NJ vs. KK/HiJ
FVB/NJ vs. LG/J
Balb/cByj vs. BTBR T+Itpr3tf/J
Balb/cByj vs. 129S1/SvmJ
Balb/cByj vs. 129X1/SvJ
Balb/cByj vs. A/J
Balb/cByj vs. AKR/J
Balb/cByj vs. C3H/HeJ
Balb/cByj vs. DBA/2j
Balb/cByj vs. NOD/ShiLtJ
Balb/cByj vs. KK/HiJ
Balb/cByj vs. LG/J
BTBR T+Itpr3tf/J vs. 129S1/SvmJ
BTBR T+Itpr3tf/J vs. 129X1/SvJ
BTBR T+Itpr3tf/J vs. A/J
BTBR T+Itpr3tf/J vs. AKR/J
BTBR T+Itpr3tf/J vs. C3H/HeJ
BTBR T+Itpr3tf/J vs. DBA/2j
BTBR T+Itpr3tf/J vs. NOD/ShiLtJ
BTBR T+Itpr3tf/J vs. KK/HiJ
BTBR T+Itpr3tf/J vs. LG/J
129S1/SvmJ vs. 129X1/SvJ
129S1/SvmJ vs. A/J
129S1/SvmJ vs. AKR/J
129S1/SvmJ vs. C3H/HeJ
129S1/SvmJ vs. DBA/2j
129S1/SvmJ vs. NOD/ShiLtJ
129S1/SvmJ vs. KK/HiJ
129S1/SvmJ vs. LG/J
129X1/SvJ vs. A/J
129X1/SvJ vs. AKR/J
129X1/SvJ vs. C3H/HeJ
129X1/SvJ vs. DBA/2j
129X1/SvJ vs. NOD/ShiLtJ
129X1/SvJ vs. KK/HiJ
129X1/SvJ vs. LG/J
A/J vs. AKR/J
A/J vs. C3H/HeJ
A/J vs. DBA/2j
A/J vs. NOD/ShiLtJ
A/J vs. KK/HiJ
A/J vs. LG/J
AKR/J vs. C3H/HeJ
AKR/J vs. DBA/2j
AKR/J vs. NOD/ShiLtJ
AKR/J vs. KK/HiJ
AKR/J vs. LG/J
C3H/HeJ vs. DBA/2j
C3H/HeJ vs. NOD/ShiLtJ
C3H/HeJ vs. KK/HiJ
C3H/HeJ vs. LG/J
DBA/2j vs. NOD/ShiLtJ
DBA/2j vs. KK/HiJ
DBA/2j vs. LG/J
NOD/ShiLtJ vs. KK/HiJ
NOD/ShiLtJ vs. LG/J
KK/HiJ vs. LG/J
Mean Diff.
-0.05167
-0.01967
-0.07567
0.01733
-0.04333
-0.024
0.05933
-0.03717
0.03867
0.03
0.3937
0.1167
0.032
-0.024
0.069
0.008333
0.02767
0.111
0.0145
0.09033
0.08167
0.4453
0.1683
-0.056
0.037
-0.02367
-0.004333
0.079
-0.0175
0.05833
0.04967
0.4133
0.1363
0.093
0.03233
0.05167
0.135
0.0385
0.1143
0.1057
0.4693
0.1923
-0.06067
-0.04133
0.042
-0.0545
0.02133
0.01267
0.3763
0.09933
0.01933
0.1027
0.006167
0.082
0.07333
0.437
0.16
0.08333
-0.01317
0.06267
0.054
0.4177
0.1407
-0.0965
-0.02067
-0.02933
0.3343
0.05733
0.07583
0.06717
0.4308
0.1538
-0.008667
0.355
0.078
0.3637
0.08667
-0.277
Fresh RBC recovery
95% CI of diff.
Result
-0.7702 to 0.6668
ns
-0.7382 to 0.6988
ns
-0.7942 to 0.6428
ns
-0.7012 to 0.7358
ns
-0.7618 to 0.6752
ns
-0.7425 to 0.6945
ns
-0.6592 to 0.7778
ns
-0.8405 to 0.7661
ns
-0.6798 to 0.7572
ns
-0.6885 to 0.7485
ns
-0.3248 to 1.112
ns
-0.6018 to 0.8352
ns
-0.6865 to 0.7505
ns
-0.7425 to 0.6945
ns
-0.6495 to 0.7875
ns
-0.7102 to 0.7268
ns
-0.6908 to 0.7462
ns
-0.6075 to 0.8295
ns
-0.7888 to 0.8178
ns
-0.6282 to 0.8088
ns
-0.6368 to 0.8002
ns
-0.2732 to 1.164
ns
-0.5502 to 0.8868
ns
-0.7745 to 0.6625
ns
-0.6815 to 0.7555
ns
-0.7422 to 0.6948
ns
-0.7228 to 0.7142
ns
-0.6395 to 0.7975
ns
-0.8208 to 0.7858
ns
-0.6602 to 0.7768
ns
-0.6688 to 0.7682
ns
-0.3052 to 1.132
ns
-0.5822 to 0.8548
ns
-0.6255 to 0.8115
ns
-0.6862 to 0.7508
ns
-0.6668 to 0.7702
ns
-0.5835 to 0.8535
ns
-0.7648 to 0.8418
ns
-0.6042 to 0.8328
ns
-0.6128 to 0.8242
ns
-0.2492 to 1.188
ns
-0.5262 to 0.9108
ns
-0.7792 to 0.6578
ns
-0.7598 to 0.6772
ns
-0.6765 to 0.7605
ns
-0.8578 to 0.7488
ns
-0.6972 to 0.7398
ns
-0.7058 to 0.7312
ns
-0.3422 to 1.095
ns
-0.6192 to 0.8178
ns
-0.6992 to 0.7378
ns
-0.6158 to 0.8212
ns
-0.7971 to 0.8095
ns
-0.6365 to 0.8005
ns
-0.6452 to 0.7918
ns
-0.2815 to 1.156
ns
-0.5585 to 0.8785
ns
-0.6352 to 0.8018
ns
-0.8165 to 0.7901
ns
-0.6558 to 0.7812
ns
-0.6645 to 0.7725
ns
-0.3008 to 1.136
ns
-0.5778 to 0.8592
ns
-0.8998 to 0.7068
ns
-0.7392 to 0.6978
ns
-0.7478 to 0.6892
ns
-0.3842 to 1.053
ns
-0.6612 to 0.7758
ns
-0.7275 to 0.8791
ns
-0.7361 to 0.8705
ns
-0.3725 to 1.234
ns
-0.6495 to 0.9571
ns
-0.7272 to 0.7098
ns
-0.3635 to 1.074
ns
-0.6405 to 0.7965
ns
-0.3548 to 1.082
ns
-0.6318 to 0.8052
ns
-0.9955 to 0.4415
ns
Adj P Value
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.7247
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.5613
0.9995
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.6639
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.4852
0.9982
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.7751
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.5882
0.9997
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.6502
> 0.9999
> 0.9999
> 0.9999
> 0.9999
0.878
> 0.9999
> 0.9999
> 0.9999
0.7493
> 0.9999
> 0.9999
0.8312
> 0.9999
0.8093
> 0.9999
0.9633
Mean Diff.
0.6696
0.05882
0.01742
0.2859
0.2967
0.2176
0.7143
0.5136
0.4519
0.3601
1.281
0.9553
-0.6107
-0.6521
-0.3837
-0.3729
-0.452
0.04473
-0.1559
-0.2177
-0.3095
0.6111
0.2858
-0.04139
0.227
0.2378
0.1588
0.6555
0.4548
0.3931
0.3012
1.222
0.8965
0.2684
0.2792
0.2002
0.6969
0.4962
0.4345
0.3426
1.263
0.9379
0.01079
-0.06828
0.4284
0.2278
0.166
0.0742
0.9948
0.6695
-0.07907
0.4176
0.217
0.1552
0.06341
0.984
0.6587
0.4967
0.2961
0.2343
0.1425
1.063
0.7378
-0.2006
-0.2624
-0.3542
0.5664
0.241
-0.06176
-0.1536
0.767
0.4417
-0.09182
0.8288
0.5034
0.9206
0.5953
-0.3253
Stored RBC recovery
95% CI of diff.
Result
0.1391 to 1.200
**
-0.4716 to 0.5892
ns
-0.5130 to 0.5478
ns
-0.2446 to 0.8163
ns
-0.2338 to 0.8271
ns
-0.3128 to 0.7480
ns
0.1839 to 1.245
**
-0.01678 to 1.044
ns
-0.07854 to 0.9823
ns
-0.1704 to 0.8905
ns
0.7502 to 1.811
****
0.4249 to 1.486
****
-1.141 to -0.08032
*
-1.183 to -0.1217
**
-0.9141 to 0.1467
ns
-0.9033 to 0.1575
ns
-0.9824 to 0.07844
ns
-0.4857 to 0.5752
ns
-0.6863 to 0.3745
ns
-0.7481 to 0.3127
ns
-0.8399 to 0.2209
ns
0.08067 to 1.142
*
-0.2447 to 0.8162
ns
-0.5718 to 0.4890
ns
-0.3034 to 0.7575
ns
-0.2926 to 0.7683
ns
-0.3717 to 0.6892
ns
0.1250 to 1.186
**
-0.07560 to 0.9853
ns
-0.1374 to 0.9235
ns
-0.2292 to 0.8317
ns
0.6914 to 1.752
****
0.3661 to 1.427
***
-0.2620 to 0.7989
ns
-0.2512 to 0.8097
ns
-0.3303 to 0.7306
ns
0.1664 to 1.227
**
-0.03420 to 1.027
ns
-0.09596 to 0.9649
ns
-0.1878 to 0.8731
ns
0.7328 to 1.794
****
0.4075 to 1.468
****
-0.5196 to 0.5412
ns
-0.5987 to 0.4621
ns
-0.1020 to 0.9589
ns
-0.3026 to 0.7582
ns
-0.3644 to 0.6964
ns
-0.4562 to 0.6046
ns
0.4644 to 1.525
****
0.1390 to 1.200
**
-0.6095 to 0.4514
ns
-0.1128 to 0.9481
ns
-0.3134 to 0.7474
ns
-0.3752 to 0.6857
ns
-0.4670 to 0.5938
ns
0.4536 to 1.514
****
0.1283 to 1.189
**
-0.03372 to 1.027
ns
-0.2344 to 0.8265
ns
-0.2961 to 0.7647
ns
-0.3879 to 0.6729
ns
0.5327 to 1.594
****
0.2073 to 1.268
**
-0.7311 to 0.3298
ns
-0.7928 to 0.2680
ns
-0.8846 to 0.1762
ns
0.03595 to 1.097
*
-0.2894 to 0.7715
ns
-0.5922 to 0.4687
ns
-0.6840 to 0.3768
ns
0.2366 to 1.297
***
-0.08874 to 0.9721
ns
-0.6222 to 0.4386
ns
0.2984 to 1.359
***
-0.02698 to 1.034
ns
0.3902 to 1.451
****
0.06484 to 1.126
*
-0.8558 to 0.2051
ns
Adj P Value
0.0053
> 0.9999
> 0.9999
0.7483
0.7045
0.9457
0.0025
0.0643
0.1525
0.4332
< 0.0001
< 0.0001
0.014
0.0071
0.3426
0.3826
0.1524
> 0.9999
0.996
0.9455
0.65
0.014
0.7487
> 0.9999
0.9282
0.9043
0.9953
0.0067
0.1468
0.31
0.6853
< 0.0001
0.0001
0.8134
0.774
0.9697
0.0033
0.0829
0.1907
0.506
< 0.0001
< 0.0001
> 0.9999
> 0.9999
0.2056
0.9268
0.9931
> 0.9999
< 0.0001
0.0053
> 0.9999
0.2343
0.9467
0.9961
> 0.9999
< 0.0001
0.0063
0.0823
0.707
0.9126
0.9982
< 0.0001
0.0016
0.9692
0.8339
0.4572
0.0287
0.8964
> 0.9999
0.9965
0.001
0.1741
> 0.9999
0.0003
0.0746
< 0.0001
0.0181
0.5811
Supplemental Table 2
Stored RBCs
Positive Correlation
docosapentaenoate (n6 DPA; 22:5n6)
cis-4-decenoyl carnitine
1-arachidonoyl-GPI (20:4)*
docosahexaenoate (DHA; 22:6n3)
palmitoyl-oleoyl-glycerophosphoglycerol (2)
1-arachidonoyl-GPE (20:4)*
17-HDoHe
1-linoleoylglycerol (18:2)
p-value
q-value
CORRELATION
2.87E-06
6.41E-06
2.75E-05
4.08E-05
4.19E-05
1.00E-04
1.00E-04
1.00E-04
2.83E-05
6.08E-05
2.00E-04
3.00E-04
3.00E-04
6.00E-04
6.00E-04
6.00E-04
6.52E-01
6.35E-01
5.99E-01
5.89E-01
5.88E-01
5.62E-01
5.55E-01
5.53E-01
alpha-tocopherol
2.00E-04
1.10E-03
5.39E-01
12-HETE
tryptophan
Negative Correlation
dodecanedioate
16-hydroxypalmitate
5-hydroxyhexanoate
sebacate (decanedioate)
2-hydroxydecanoate
2-aminoheptanoate
caproate (6:0)
heptanoate (7:0)
caprylate (8:0)
2-hydroxyoctanoate
undecanedioate
pelargonate (9:0)
13-HODE + 9-HODE
9,10-DiHOME
8-hydroxyoctanoate
pentadecanoate (15:0)
azelate (nonanedioate)
alpha-hydroxycaproate
hexadecanedioate
suberate (octanedioate)
3-hydroxysebacate
2-hydroxypalmitate
4-hydroxy-nonenal-glutathione
indole-3-carboxylic acid
pimelate (heptanedioate)
4-hydroxybutyrate (GHB)
glutarate (pentanedioate)
5-HETE
palmitoleate (16:1n7)
phenylalanylglycine
2-oxoadipate
2-hydroxyadipate
4-methyl-2-oxopentanoate
tetradecanedioate
1-palmitoylglycerol (16:0)
xanthine
cis-vaccenate (18:1n7)
caprate (10:0)
arachidate (20:0)
myristate (14:0)
methionine sulfoxide
palmitate (16:0)
glycerol 3-phosphate
1-oleoyl-GPI (18:1)*
1-palmitoyl-GPI (16:0)*
6-oxopiperidine-2-carboxylic acid
10-heptadecenoate (17:1n7)
3-methyl-2-oxobutyrate
4-hydroxy-2-nonenal
3.00E-04
5.00E-04
1.50E-03
2.30E-03
1.80E-14
8.40E-14
1.17E-13
1.71E-12
2.39E-12
5.55E-12
1.01E-10
1.18E-10
1.28E-10
1.89E-10
1.99E-10
5.51E-10
1.65E-09
4.60E-09
1.33E-08
6.51E-08
7.31E-08
9.40E-08
1.18E-07
1.58E-07
1.63E-07
5.99E-07
6.64E-07
8.70E-07
9.77E-07
8.34E-06
1.23E-05
1.60E-05
1.89E-05
2.05E-05
4.15E-05
4.18E-05
1.00E-04
1.00E-04
2.00E-04
2.00E-04
2.00E-04
2.00E-04
3.00E-04
3.00E-04
4.00E-04
4.00E-04
5.00E-04
5.00E-04
5.00E-04
6.00E-04
6.00E-04
7.00E-04
7.00E-04
Fresh RBCs
Positive Correlation
aspartate
2'-deoxyuridine
deoxycarnitine
glycylleucine
trans-4-hydroxyproline
thymidine
isoleucylglycine
gamma-glutamyltyrosine
valylglycine
N6-acetyllysine
glutamine
N-acetyltaurine
N-acetylglycine
5,6-dihydrothymine
Negative Correlation
palmitate (16:0)
Super Pathway
Sub Pathway
Polyunsaturated Fatty Acid (n3 and n6)
Fatty Acid Metabolism(Acyl Carnitine)
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
Phosphatidylglycerol
Lysolipid
Fatty Acid, Monohydroxy
Monoacylglycerol
5.35E-01
5.12E-01
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Cofactors and
Vitamins
Lipid
Amino Acid
4.72E-12
9.99E-12
9.99E-12
1.10E-10
1.22E-10
2.37E-10
3.64E-09
3.64E-09
3.64E-09
4.64E-09
4.64E-09
1.18E-08
3.25E-08
8.42E-08
2.27E-07
1.04E-06
1.10E-06
1.34E-06
1.59E-06
1.99E-06
1.99E-06
6.98E-06
7.40E-06
9.29E-06
1.00E-05
7.63E-05
1.00E-04
1.00E-04
2.00E-04
2.00E-04
3.00E-04
3.00E-04
6.00E-04
6.00E-04
1.10E-03
1.10E-03
1.10E-03
1.10E-03
1.50E-03
1.50E-03
2.00E-03
2.00E-03
2.30E-03
2.30E-03
2.30E-03
2.70E-03
2.70E-03
3.00E-03
3.00E-03
-8.79E-01
-8.69E-01
-8.67E-01
-8.46E-01
-8.43E-01
-8.36E-01
-8.08E-01
-8.06E-01
-8.05E-01
-8.01E-01
-8.01E-01
-7.89E-01
-7.75E-01
-7.62E-01
-7.47E-01
-7.23E-01
-7.21E-01
-7.17E-01
-7.13E-01
-7.08E-01
-7.07E-01
-6.84E-01
-6.82E-01
-6.77E-01
-6.74E-01
-6.28E-01
-6.19E-01
-6.13E-01
-6.09E-01
-6.07E-01
-5.89E-01
-5.88E-01
-5.63E-01
-5.55E-01
-5.51E-01
-5.50E-01
-5.39E-01
-5.39E-01
-5.32E-01
-5.29E-01
-5.24E-01
-5.18E-01
-5.16E-01
-5.16E-01
-5.16E-01
-5.09E-01
-5.08E-01
-5.02E-01
-5.02E-01
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Amino Acid
Amino Acid
Lipid
Lipid
Amino Acid
Lipid
Lipid
Peptide
Amino Acid
Lipid
Amino Acid
Lipid
Lipid
Nucleotide
Lipid
Lipid
Lipid
Lipid
Amino Acid
Lipid
Lipid
Lipid
Lipid
Amino Acid
Lipid
Amino Acid
Lipid
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Amino
Medium Chain Fatty Acid
Medium Chain Fatty Acid
Medium Chain Fatty Acid
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Medium Chain Fatty Acid
Fatty Acid, Monohydroxy
Fatty Acid, Dihydroxy
Fatty Acid, Monohydroxy
Long Chain Fatty Acid
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Monohydroxy
Glutathione Metabolism
Tryptophan Metabolism
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Lysine Metabolism
Eicosanoid
Long Chain Fatty Acid
Dipeptide
Lysine Metabolism
Fatty Acid, Dicarboxylate
Leucine, Isoleucine and Valine Metabolism
Fatty Acid, Dicarboxylate
Monoacylglycerol
Purine Metabolism, (Hypo)Xanthine/Inosine containing
Long Chain Fatty Acid
Medium Chain Fatty Acid
Long Chain Fatty Acid
Long Chain Fatty Acid
Methionine, Cysteine, SAM and Taurine Metabolism
Long Chain Fatty Acid
Glycerolipid Metabolism
Lysolipid
Lysolipid
Lysine Metabolism
Long Chain Fatty Acid
Leucine, Isoleucine and Valine Metabolism
Fatty Acid, Oxidized
p-value
q-value
CORRELATION
1.11E-06
9.78E-06
2.00E-04
3.00E-04
4.00E-04
4.00E-04
5.00E-04
6.00E-04
7.00E-04
9.00E-04
9.00E-04
9.00E-04
1.20E-03
1.30E-03
3.00E-04
9.00E-04
4.00E-03
4.90E-03
5.30E-03
5.30E-03
5.80E-03
6.40E-03
7.20E-03
7.60E-03
7.60E-03
7.60E-03
9.30E-03
9.50E-03
7.12E-01
6.65E-01
5.81E-01
5.67E-01
5.59E-01
5.56E-01
5.51E-01
5.44E-01
5.41E-01
5.31E-01
5.31E-01
5.29E-01
5.19E-01
5.15E-01
7.22E-06
9.00E-04
-0.67
Tocopherol Metabolism
Eicosanoid
Tryptophan Metabolism
Super Pathway
Sub Pathway
Amino Acid
Nucleotide
Lipid
Peptide
Amino Acid
Nucleotide
Peptide
Peptide
Peptide
Amino Acid
Amino Acid
Amino Acid
Amino Acid
Nucleotide
Alanine and Aspartate Metabolism
Pyrimidine Metabolism, Uracil Containing
Carnitine Metabolism
Dipeptide
Urea cycle; Arginine and Proline Metabolism
Pyrimidine Metabolism, Thymine containing
Dipeptide
Gamma-glutamyl Amino Acid
Dipeptide
Lysine Metabolism
Glutamate Metabolism
Methionine, Cysteine, SAM and Taurine Metabolism
Glycine, Serine and Threonine Metabolism
Pyrimidine Metabolism, Thymine containing
Lipid
Long Chain Fatty Acid
Supplemental Table 2
glycerol 3-phosphate
alpha-ketoglutarate
palmitoleate (16:1n7)
stearate (18:0)
1-oleoylglycerol (18:1)
linoleate (18:2n6)
eicosenoate (20:1)
10-heptadecenoate (17:1n7)
dihomo-linoleate (20:2n6)
alpha-tocopherol
4-hydroxy-nonenal-glutathione
20a-dihydroprogesterone
margarate (17:0)
4-methyl-2-oxopentanoate
2-phosphoglycerate
oleate (18:1n9)
linolenate [alpha or gamma; (18:3n3 or 6)]
3-methyl-2-oxobutyrate
cis-vaccenate (18:1n7)
10-nonadecenoate (19:1n9)
succinylcarnitine
3-methyl-2-oxovalerate
2-oleoylglycerol (18:1)
1.40E-05
2.47E-05
7.92E-05
9.83E-05
1.00E-04
1.00E-04
1.00E-04
2.00E-04
2.00E-04
2.00E-04
3.00E-04
3.00E-04
4.00E-04
4.00E-04
5.00E-04
5.00E-04
6.00E-04
8.00E-04
8.00E-04
9.00E-04
1.10E-03
1.10E-03
1.30E-03
1.00E-03
1.40E-03
2.80E-03
2.80E-03
2.80E-03
2.80E-03
2.80E-03
4.00E-03
4.00E-03
4.00E-03
4.90E-03
4.90E-03
5.30E-03
5.30E-03
5.80E-03
5.80E-03
6.40E-03
7.60E-03
7.60E-03
7.60E-03
8.80E-03
8.80E-03
9.50E-03
-0.66
-0.64
-0.61
-0.60
-0.60
-0.60
-0.59
-0.59
-0.58
-0.58
-0.57
-0.56
-0.56
-0.56
-0.55
-0.55
-0.55
-0.53
-0.53
-0.53
-0.52
-0.52
-0.52
Lipid
Energy
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Lipid
Vitamin
Amino Acid
Lipid
Lipid
Amino Acid
Carbohydrate
Lipid
Lipid
Amino Acid
Lipid
Lipid
Energy
Amino Acid
Lipid
Glycerolipid Metabolism
TCA Cycle
Long Chain Fatty Acid
Long Chain Fatty Acid
Monoacylglycerol
Polyunsaturated Fatty Acid (n3 and n6)
Long Chain Fatty Acid
Long Chain Fatty Acid
Polyunsaturated Fatty Acid (n3 and n6)
Tocopherol
Glutathione Metabolism
Steroid
Long Chain Fatty Acid
Leucine, Isoleucine and Valine Metabolism
Glycolysis, Gluconeogenesis, and Pyruvate Metabolism
Long Chain Fatty Acid
Polyunsaturated Fatty Acid (n3 and n6)
Leucine, Isoleucine and Valine Metabolism
Long Chain Fatty Acid
Long Chain Fatty Acid
TCA Cycle
Leucine, Isoleucine and Valine Metabolism
Monoacylglycerol
Ratio of Stored to Fresh
Positive Correlation
1-arachidonoyl-GPI (20:4)*
dihomo-linolenate (20:3n3 or n6)
1-linoleoylglycerol (18:2)
12-HETE
alpha-tocopherol
1-arachidonoyl-GPE (20:4)*
docosahexaenoate (DHA; 22:6n3)
glutathione, reduced (GSH)
adrenate (22:4n6)
1-linoleoyl-GPE (18:2)*
docosapentaenoate (n6 DPA; 22:5n6)
docosapentaenoate (n3 DPA; 22:5n3)
17-HDoHe
1-linoleoyl-GPI (18:2)*
cis-4-decenoyl carnitine
stearoyl-arachidonoyl-glycerophosphocholine(2)
2-oleoylglycerol (18:1)
p-value
q-value
CORRELATION
Super Pathway
Sub Pathway
4.17E-06
5.49E-06
6.43E-06
1.41E-05
1.41E-05
1.83E-05
3.34E-05
6.88E-05
7.83E-05
2.00E-04
3.00E-04
5.00E-04
5.00E-04
6.00E-04
8.00E-04
1.20E-03
1.20E-03
5.35E-05
6.52E-05
6.95E-05
1.00E-04
1.00E-04
2.00E-04
3.00E-04
5.00E-04
6.00E-04
1.30E-03
1.90E-03
2.90E-03
2.90E-03
3.20E-03
4.20E-03
5.70E-03
5.70E-03
6.77E-01
6.71E-01
6.67E-01
6.49E-01
6.49E-01
6.42E-01
6.27E-01
6.07E-01
6.03E-01
5.79E-01
5.65E-01
5.48E-01
5.47E-01
5.36E-01
5.28E-01
5.13E-01
5.11E-01
lipid
lipid
lipid
lipid
Vitamin
lipid
lipid
Amino Acid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
Lysolipid
Eicosanoid
Tocopherol
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
glutathione metabolism
Polyunsaturated Fatty Acid (n3 and n6)
Lysolipid
Polyunsaturated Fatty Acid (n3 and n6)
Polyunsaturated Fatty Acid (n3 and n6)
Fatty Acid, Monohydroxy
Lysolipid
Fatty Acid Metabolism (Acyl Carnitines)
Phosphatidylcholine Metabolism
monoacylglycerol
Negative Correlation
undecanedioate
sebacate (decanedioate)
5-hydroxyhexanoate
2-aminoheptanoate
2-hydroxydecanoate
azelate (nonanedioate)
suberate (octanedioate)
2-hydroxyoctanoate
caprylate (8:0)
heptanoate (7:0)
8-hydroxyoctanoate
16-hydroxypalmitate
kynurenine
indole-3-carboxylic acid
2-hydroxypalmitate
N6-succinyladenosine
glutarate (pentanedioate)
pelargonate (9:0)
pimelate (heptanedioate)
hexadecanedioate
dodecanedioate
3-hydroxysebacate
caproate (6:0)
glycolate (hydroxyacetate)
4-hydroxy-nonenal-glutathione
N6-acetyllysine
2-hydroxystearate
9,10-DiHOME
alpha-hydroxycaproate
glycylvaline
2-hydroxybutyrate (AHB)
aspartate
uracil
1.15E-10
5.01E-10
1.90E-09
2.67E-09
3.18E-09
1.96E-08
2.48E-08
2.76E-08
4.19E-08
9.66E-08
2.23E-07
2.98E-07
3.71E-07
1.05E-06
1.29E-06
1.87E-06
2.82E-06
4.28E-06
6.29E-06
2.23E-05
2.45E-05
4.49E-05
6.96E-05
7.31E-05
1.00E-04
1.00E-04
3.00E-04
5.00E-04
6.00E-04
6.00E-04
1.00E-03
1.00E-03
1.00E-03
2.73E-08
5.95E-08
1.51E-07
1.51E-07
1.51E-07
7.76E-07
8.20E-07
8.20E-07
1.11E-06
2.30E-06
4.82E-06
5.90E-06
6.78E-06
1.78E-05
2.04E-05
2.78E-05
3.94E-05
5.35E-05
6.95E-05
2.00E-04
2.00E-04
4.00E-04
5.00E-04
5.00E-04
7.00E-04
7.00E-04
1.90E-03
2.90E-03
3.20E-03
3.20E-03
5.00E-03
5.00E-03
5.00E-03
-8.36E-01
-8.21E-01
-8.05E-01
-8.01E-01
-7.99E-01
-7.74E-01
-7.70E-01
-7.69E-01
-7.62E-01
-7.49E-01
-7.35E-01
-7.30E-01
-7.26E-01
-7.06E-01
-7.02E-01
-6.94E-01
-6.86E-01
-6.77E-01
-6.68E-01
-6.37E-01
-6.35E-01
-6.19E-01
-6.06E-01
-6.05E-01
-5.93E-01
-5.87E-01
-5.58E-01
-5.44E-01
-5.39E-01
-5.36E-01
-5.21E-01
-5.20E-01
-5.17E-01
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
lipid
amino acid
amino acid
lipid
nucleotide
amino acid
lipid
lipid
lipid
lipid
lipid
lipid
Xenobiotic
amino acid
amino acid
lipid
lipid
lipid
peptide
amino acid
amino acid
nucleotide
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Fatty Acid, Amino
Fatty Acid, Monohydroxy
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Medium Chain Fatty Acid
Medium Chain Fatty Acid
Fatty Acid, Monohydroxy
Fatty Acid, Monohydroxy
Tryptophan Metabolism
Tryptophan Metabolism
Fatty Acid, Monohydroxy
Purine Metabolism
Lysine Metabolism
Medium Chain Fatty Acid
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Dicarboxylate
Fatty Acid, Monohydroxy
Medium Chain Fatty Acid
Chemical
Glutathione Metabolism
Lysine Metabolism
Fatty Acid, Monohydroxy
Fatty Acid, Dihyrdoxy
Fatty Acid, Monohydroxy
dipeptide
Methionine, Cysteine, SAM and Taurine Metabolism
Alanine and Aspartate Metabolism
Pyrimidine Metabolism, Uracil containing
Supplemental Table 1: ANOVA analysis of statistical significance in differences of 24 hr RBC
recoveries between strains for fresh or stored RBCs.
Recoveries of stored RBCs were
compared for differences in mean of log10-transformed data.
No significant differences were
observed for any fresh RBCs. Significant differences for stored RBCs are indicated by shading.
All values show combined data of all three experiments shown in figure 1.
Supplemental Table 2: All analytes that correlated with 24 hr RBC recoveries of stored RBCs
that have a Pearson’s coefficient of greater than 0.5 or lesser than -0.5, and also had p values
of less than 0.05 and q values of less than 0.01 are shown. Lists are broken down as to
“positive correlations” and “negative correlations” of the indicated analytes with 24-hour
recoveries of transfused stored RBCs with regards to analytes measured in (Stored RBCs),
(Fresh RBCs), or the (Ratio of Stored to Fresh RBCs). All correlations were performed with 24hour recoveries of stored RBCs. Thus, the correlations for (Fresh RBCs) are the levels of
measured analytes at time of collection correlated to the 24 hour recoveries obtained 7 days
later after storage. All values show combined data of all three experiments shown in figure 1.
Supplemental Methods
Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS):
The
LC/MS
platform
was
based
on
a
Waters
ACQUITY
ultra-performance
liquid
chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass
spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap
mass analyzer operated at 35,000 mass resolution.
The sample extract was dried then
reconstituted in acidic or basic LC-compatible solvents, each of which contained 8 or more
injection standards at fixed concentrations to ensure injection and chromatographic consistency.
One aliquot was analyzed using acidic positive ion optimized conditions and the other using
basic negative ion optimized conditions in two independent injections using separate dedicated
columns (Waters UPLC BEH C18-2.1x100 mm, 1.7 µm).
Extracts reconstituted in acidic
conditions were gradient eluted from a C18 column using water and methanol containing 0.1%
formic acid. The basic extracts were similarly eluted from C18 using methanol and water,
however with 6.5mM Ammonium Bicarbonate. The third aliquot was analyzed via negative
ionization following elution from a HILIC column (Waters UPLC BEH Amide 2.1x150 mm, 1.7
µm) using a gradient consisting of water and acetonitrile with 10mM Ammonium Formate. The
MS analysis alternated between MS and data-dependent MS2 scans using dynamic exclusion,
and the scan range was from 80-1000 m/z.
Gas Chromatography-Mass Spectroscopy (GC-MS): The samples destined for analysis by GCMS were dried under vacuum for a minimum of 18 h prior to being derivatized under dried
nitrogen using bistrimethyl-silyltrifluoroacetamide. Derivatized samples were separated on a 5%
diphenyl / 95% dimethyl polysiloxane fused silica column (20 m x 0.18 mm ID; 0.18 um film
thickness) with helium as carrier gas and a temperature ramp from 60° to 340°C in a 17.5 min
period. Samples were analyzed on a Thermo-Finnigan Trace DSQ fast-scanning single-
quadrupole mass spectrometer using electron impact ionization (EI) and operated at unit mass
resolving power. The scan range was from 50–750 m/z.