Integrated Metabolomic and Gut Microbiome Profiles Reveal Postmortem Biomarkers of Fatal Anaphylaxis

Abstract

The incidence of fatal anaphylaxis is increasing, but there is still no recognized "golden standard" for forensic diagnosis. Due to its non-specific symptoms, especially cardiovascular symptoms without cutaneous changes, it can easily be misdiagnosed as acute myocardial infarction. Here, we established rat models (n = 12) of fatal anaphylaxis (FA), acute myocardial infarction (AMI), and coronary atherosclerosis with anaphylaxis (CAA). The untargeted metabolomics of plasma and 16S rRNA sequencing of fecal matter was performed, and a random forest was used to identify potential biomarkers. Three metabolites (tryptophan, trans-3-indole acrylic acid, and imidazole acetic acid) and three microbial genera (g_Prevotellaceae_Ga6A1_group, g_UCG_008, and g_Eubacterium_hallii_group) were identified as potential biomarkers for distinguishing anaphylaxis and non-anaphylaxis. The classification model of plasma metabolites showed a much better discriminatory performance than that of microbial genus, serum IgE, and tryptase. The performance of the microbial genera was superior to the serum IgE but inferior to the serum tryptase. Forensic samples of fatal anaphylaxis and non-anaphylaxis deaths (n = 12) were collected for untargeted metabolomics detection. The results showed that among the three identified metabolic biomarkers, tryptophan has better stability in cadaveric blood samples. Its diagnostic performance (AUC = 87.1528) was superior to serum IgE and tryptase, making it more suitable as a postmortem biomarker of fatal anaphylaxis.

Keywords: acute myocardial infarction; biomarker; fatal anaphylaxis; forensic pathology; gut microbiome; metabolomics.

Figure 1

The characteristics of fatal anaphylaxis: (A) Schematic diagram of rat model preparation. (B) The cyanotic mouth, nose, and auricle of fatal anaphylaxis rats after the OVA challenge. (C) Serum IgE and tryptase of rats. * p < 0.05 vs. control, ** p < 0.01 vs. control, *** p < 0.001 vs. control, # p < 0.05 vs. FA, ## p < 0.01 vs. FA. (D) The representative sections of a lung stained with HE (200×) and tryptase IHC (400×). LAD: left anterior descending coronary artery.

Figure 2

The characteristics of high-fat-diet rats and after coronary artery ligation: (A) The serum lipid levels in high-fat diet rats, including TC, TG, LDL, and HDL. (B) The serum atherosclerosis index in high-fat-diet rats. (C) Myocardial ischemia and pallor in the left ventricle after ligation of LAD. (D) The representative electrocardiograms of each group. (E) The representative sections of the coronary artery and myocardium stained with HE (200×). (F) The representative sections of the aortic valve (50×), aortic arch (100×), and coronary artery (200×) stained with oil red O. The arrows show the atherosclerotic plaques stained bright red with oil red O. “ns” represents no significance, *** p < 0.001, **** p < 0.0001. TC, total cholesterol; TG, triglyceride; LDL, low-density lipoprotein; HDL, high-density lipoprotein; AI, atherosclerosis index.

Figure 3

The analysis of metabolomics. (A) OPLS-DA scatter plot of overall samples. (B) The Venn diagram of differential metabolites. (C) The MetPA diagrams.

Figure 4

The altered metabolites and perturbed metabolic pathways. The altered metabolites were labeled with up-regulated (↑) and down-regulated (↓). The red, blue, and green arrows indicate changes in the FA, AMI, and CAA groups, respectively. The green text indicates perturbed metabolic pathways.

Figure 5

The altered gut microbiota. (A) The Venn diagram of ASVs. (B) The taxonomy analysis tree. The colored sectors represent different groups, and the size of each sector indicates the proportional abundance at the taxonomic level. The first number under the circle denotes the count of sequences that only align with that specific classification (not to a lower classification rank), and the second number indicates the total count of aligned sequences. (C) The violin diagrams of alpha diversity. Each box plot showed the minimum, first quartile, median, third quartile, and maximum value of the sample index in the group. ** p < 0.01. (D) The PCoA analysis based on Bray–Curtis distances indicated the beta diversity. (E) The cladogram. The bar chart shows the classification of species with significant effects in different groups. The colored nodes in the branches represent the microbiota that plays an important role in each group, and the yellow nodes represent the adiaphorous microbiota.

Figure 6

The random forest classification model. (A) The feature importance ranking: 1, anaphylaxis (including the FA and CAA groups); 0, non-anaphylaxis (including the CON and AMI groups). (B) Validation ROC curves of the random forest classification model consisting of the most important three microbial genera and three metabolites.

Figure 7

Integrated networks of metabolites and gut microbiota. The size of the circle in the network represents the degree of connectivity, while the thickness of the line represents the strength of the correlation. (A) Integrated networks of the FA group. (B) Integrated networks of the AMI group. (C) Integrated networks of the CAA group.

Figure 8

(A) The abundance of tryptophan in different causes of death. **** p < 0.0001. (B) The ROC curve showed the diagnostic performance of tryptophan in distinguishing FA from non-FA better than serum IgE and tryptase.