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. 2021 Jun 12;5(7):e591.
doi: 10.1097/HS9.0000000000000591. eCollection 2021 Jul.

Metabolic Fingerprint in Hereditary Spherocytosis Correlates With Red Blood Cell Characteristics and Clinical Severity

Birgit van Dooijeweert  1   2 , Melissa H Broeks  3 , Nanda M Verhoeven-Duif  3 , Wouter W van Solinge  1 , Eduard J van Beers  4 , Minke A E Rab  1   4 , Edward E S Nieuwenhuis  2 , Judith J M Jans  3 , Marije Bartels  2   4 , Richard van Wijk  1
Affiliations

Metabolic Fingerprint in Hereditary Spherocytosis Correlates With Red Blood Cell Characteristics and Clinical Severity

Birgit van Dooijeweert et al. Hemasphere. .
No abstract available

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Figures

Figure 1.
Figure 1.
Metabolic profile in DBS of HS patients. (A), PCA plot and (B) PLS-DA plot of HS and HCs displayed with 95% confidence regions. Both analyses reduce dimensionality to identify the overall variation by combining all metabolite features (weighted) into new variables. These new variables are principal components. The first 2 principal components capture most of the variation in the dataset, expressed as percentage of total variation within a dataset, and are displayed on the x- and y-axis. Each dot represents a patient or control sample, colored according to group label. The position of these dots is based on the metabolite profile of 1770 unique Z scores. Samples that have a similar metabolic profile cluster more closely. The difference between PCA and PLS-DA is that PLS-DA takes group label into account to find the optimal separation between groups. (C), The metabolites that contribute the most to separation in PLS-DA are identified by a high VIP score. The 30 features that contribute the most to separation of patients and HC are displayed. (D), Heatmap of 30 most significant features identified by t test (P < 0.000003). Each colored cell in the heatmap corresponds to the autoscaled Z score per metabolite feature (rows). The columns of the heatmap are colored by group label. The heatmap was created with hierarchical Ward’s linkage clustering using Euclidean distances. The dendrogram represents clustering of samples and metabolite features. Figures were created using MetaboAnalyst. A comprehensive overview of P values and isomers is displayed in Supplemental Table 2 (http://links.lww.com/HS/A158). DBS = dried blood spot; HC = healthy control; HS = hereditary spherocytosis; PCA = principal component analysis; PLS-DA = partial least squares discriminant analysis; VIP = Variable Importance in Projection.
Figure 2.
Figure 2.
Metabolic profile in relation to clinical severity phenotypes. (A), PCA plot and (B) PLS-DA plot distinguishing clinical severity. (C), Top 20 features contributing to the separation of patients and controls in PLS-DA, reflected by VIP-scores. For almost all metabolites a correlation with clinical severity is observed, reflected by an increasing or decreasing color gradient. (D), Z scores of spermidine, N1-Acetylspermidine, L-Acetylcarnitine and Propionylcarnitine based on clinical severity for control (n = 50), HS-mild (n = 15), HS-moderate (n = 12) and HS-severe (n = 8) in a boxplot with Tukey whiskers. HS = hereditary spherocytosis; PCA = principal component analysis; PLS-DA = partial least squares discriminant analysis; VIP = Variable Importance in Projection.
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