Unsupervised analysis of combined lipid and coagulation data reveals coagulopathy subtypes among dialysis patients

Contaifer, Daniel; Carl, Daniel; Warncke, Urszula Osinska; Martin, Erika J.; Mohammed, Bassem M.; Tassell, Benjamin Van; Brophy, Donald F.; Chalfant, Charles E.; Wijesinghe, Dayanjan S.

doi:10.1194/jlr.p068833

Cited by 12 publications

(11 citation statements)

References 34 publications

(34 reference statements)

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“…The strategy used in our study to enable this goal investigated the plasma metabolome and lipidome to profile SCT patients. This approach resulted in the generation of complex and multidimensional data that required the use of multivariate statistical approaches to decrease dimensional space, a common approach in metabolomic and lipidomic studies 34,35 . The predictors and potential biomarkers of GVHD found in the plasma of patients pre-transplant indicate that the metabolic profile prior to bone marrow transplant is a major influence in their clinical course following transplantation and can be used to correlate immune and metabolic phenotype.…”

Section: Discussionmentioning

confidence: 99%

Risk stratification of allogeneic stem cell recipients with respect to the potential for development of GVHD via their pre-transplant plasma lipid and metabolic signature

Contaifer

et al. 2018

Preprint

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The clinical outcome of allogeneic hematopoietic stem cell transplantation (SCT) is strongly influenced from the complications arising during the post-transplant immune restoration and has been well studied and described. However, the metabolic status of the recipient pre-transplant also has the potential to influence this outcome and has never been studied before and has the potential to enable risk stratification with respect to the development of transplant associated complications such as graft vs. host disease (GVHD). In order to better understand this aspect of transplant related complications we investigated the pre-transplantation metabolic signature to assess the possibility of pre-transplant risk stratification. This pilot study was composed of 14 patients undergoing myeloablative conditioning followed by either HLA matched related, unrelated donor, or autologous stem cell transplantation. Blood samples were taken prior to transplant and the plasma was comprehensively characterized with respect to its lipidome and metabolome via LCMS and GCMS. The results indicated a significantly pro-inflammatory metabolic profile in patients who eventually developed Graft vs. Host Disease (GVHD). The data revealed 5 potential pre-transplant biomarkers (1-monopalmitin, diacylglycerol (DG) 38:5, DG 38:6, 2-aminobutyric acid, and fatty acid (FA) 20:1) that demonstrated high sensitivity and specificity towards predicting post-transplant GVHD development. The predictive model developed demonstrated an estimated predictive accuracy of risk stratification of 100%, with an Area under the Curve of the ROC of 0.995 with 100%. The likelihood ratio of 1-monopalmitin (infinity), DG 38:5 (6.0) and DG 38:6 (6.0) also demonstrated that a patient with a positive test result for these biomarkers pre-transplant will likely have very high odds of developing GVHD post-transplant. Collectively the data demonstrates the possibility of using pre-transplant metabolic signature for risk stratification of SCT recipients with respect to development of GVHD.Recent studies have demonstrated that a dynamical systems model of T cell reconstitution may allow understanding alloreactivity in terms of antigenic differences between donors and recipients and ensuing T cell responses [27][28][29] . This model incorporates the idea that when T cells become activated and undergo metabolic changes upon antigen encounter, they may increase mass, and this appears to be the case when T cell masses are measured following allogeneic SCT 30 . This change in mass is likely driven by the cytokine and chemokine milieu in these patients, which is likely to be altered because of conditioning chemotherapy and radiation induced tissue damage. Further chemokine release is mediated by the effects of inflammation due to infections and endothelial injury. These changes in the post-transplant milieu may be investigated through the study of the metabolomic and lipidomic profile. In this paper we describe the lipidomic and metabolomic profiles of patients undergoing myeloablativ...

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Section: Discussionmentioning

confidence: 99%

Risk stratification of allogeneic stem cell recipients with respect to the potential for development of GVHD via their pre-transplant plasma lipid and metabolic signature

Contaifer

et al. 2018

Preprint

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“…Statistical validation suggests that DSA, LPE (16:0) and PC (18:0/20:4) are putative biomarkers that should be further tested in a prospective clinical study. These biomarkers could indicate a state of increased inflammation associated with chronic kidney disease and hemodialysis in selected groups of patients compared with others(15).…”

Section: Discussionmentioning

confidence: 99%

A Pre-transplant Blood-based Lipid Signature for Prediction of Antibody-mediated Rejection in Kidney Transplant Patients

sultan

Contaifer

Morriss

et al. 2018

Preprint

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There is a lack of biomarkers for pre-kidney transplant immune risk stratification to avoid over- or under-immunosuppression. Since the circulating lipidome is integrally involved in inflammation, we hypothesized that the lipidome may provide biomarkers that are helpful in the prediction of antibody-mediated rejection. We used mass spectrometry to detect the plasma lipidome in samples collected over 1 year post-kidney transplant from a prospective, observational cohort of adult kidney transplant recipients (KTR), classified in two groups, one with antibody mediated rejection (AMR) and the other with stable graft function (SC). We used linear discriminant analysis to generate predictive models of rejection. A ‘lipid-only’ model generated from samples taken on day of transplant (T1) revealed a seven lipid classifier (lysophosphatidylethanolamine and phosphatidylcholine species) with misclassification rate of 8.9% [AUC = 0.95 (95% CI = 0.84-0.98), R2 = 0.63]. A clinical model [(using donor specific antibody (DSA) and panel reactive antibody (PRA)] was inferior with a misclassification rate of 15.6% [AUC = 0.82 (95% CI = 0.69-0.93), R2 = 0.41]. A combined model using four lipid classifiers and DSA improved the AUC further to 0.98 (95% CI = 0.89-1.0, R2 = 0.83) with a misclassification of only 2.2%. The polyunsaturated phospholipid subspecies that discriminated the two groups were much lower in the AMR group when compared to the SC group. While the lipidomic profile changed significantly among SC patients on serial sampling post-transplant, such changes were not seen in AMR patients. After taking serial lipidomic changes overtime in SC patients in to account, the AMR group still showed sustained decreased levels of specific lipids at the time of AMR. These findings suggest that a lack of anti-inflammatory polyunsaturated phospholipids could identify patients at a higher risk of AMR at the time of transplant.

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“…Sphingolipids were prepared and analyzed as previously described [39][40][41]. Briefly, a 200 μl aliquot of PBS was added to the cell pellet and transferred to glass screwcap vials.…”

Section: Sphingolipidomics Analysesmentioning

confidence: 99%

Upregulation of human glycolipid transfer protein (GLTP) induces necroptosis in colon carcinoma cells

Mishra

Stephenson

Chalfant

et al. 2019

Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biolog

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Human GLTP on chromosome 12 (locus 12q24.11) encodes a 24 kD amphitropic lipid transfer protein (GLTP) that mediates glycosphingolipid (GSL) intermembrane trafficking and regulates GSL homeostatic levels within cells. Herein, we provide evidence that GLTP overexpression inhibits the growth of human colon carcinoma cells (HT-29; HCT-116), but spares normal colonic cells (CCD-18Co). Mechanistic studies reveal that GLTP overexpression arrested the cell cycle at the G1/S checkpoint via upregulation of cyclin-dependent kinase inhibitor-1B (Kip1/p27) and cyclin-dependent kinase inhibitor 1A (Cip1/p21) at the protein and mRNA levels, and downregulation of cyclin-dependent kinase-2 (CDK2), cyclin-dependent kinase-4 (CDK4), cyclin E and cyclin D1 protein levels. Assessment of the biological fate of HCT-116 cells overexpressing GLTP indicated no increase in cell death suggesting induction of quiescence. However, HT-29 cells overexpressing GLTP underwent cell death by necroptosis as revealed by phosphorylation of human mixed lineage kinase domain-like protein (pMLKL) via receptor-interacting protein kinase-3 (RIPK-3), elevated cytosolic calcium, and plasma membrane permeabilization by pMLKL oligomerization. Overexpression of W96A-GLTP, an ablated GSL binding site mutant,

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Unsupervised analysis of combined lipid and coagulation data reveals coagulopathy subtypes among dialysis patients

Cited by 12 publications

References 34 publications

Risk stratification of allogeneic stem cell recipients with respect to the potential for development of GVHD via their pre-transplant plasma lipid and metabolic signature

Risk stratification of allogeneic stem cell recipients with respect to the potential for development of GVHD via their pre-transplant plasma lipid and metabolic signature

A Pre-transplant Blood-based Lipid Signature for Prediction of Antibody-mediated Rejection in Kidney Transplant Patients

Upregulation of human glycolipid transfer protein (GLTP) induces necroptosis in colon carcinoma cells

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