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. 2021 Apr;44(4):429-440.
doi: 10.1111/jfd.13288. Epub 2020 Oct 26.

A multi-biomarker study on Atlantic salmon (Salmo salar L.) affected by the emerging Red Skin Disease in the Baltic Sea

Fabian G Weichert  1 , Charlotte Axén  2 , Lars Förlin  1 , Pedro A Inostroza  1 , Ulrike Kammann  3 , Annikki Welling  4 , Joachim Sturve  1 , Noomi Asker  1
Affiliations

A multi-biomarker study on Atlantic salmon (Salmo salar L.) affected by the emerging Red Skin Disease in the Baltic Sea

Fabian G Weichert et al. J Fish Dis. 2021 Apr.

Abstract

For half a decade, the Atlantic salmon in the Baltic Sea has been facing severe health issues. Clinical signs like haemorrhage, erosions and ulcerative/necrotic skin conditions in returning adults have been reported from different Swedish rivers. These primary disease signs precede a secondary, terminal fungal infection. As initial investigations of the disease did not provide conclusive answers regarding the pathogenesis, this study was initiated to gain insight into a possible link between this so-called Red Skin Disease and anthropogenic influences. Therefore, returning salmon were caught in rivers along the Swedish coast and different tissues were sampled. The focus was put on the measurements of a battery of biomarkers as well as biochemical and haematological parameters, which were analysed using multivariate statistics. The main findings were a severe osmotic haemodilution, an immune response and an alteration of the carbohydrate metabolism in diseased fish. Furthermore, oxidative stress does not seem to be a likely factor in the pathogenesis. Concluding, certain changes in physiological parameters were shown to be indicative for the disease patterns, while others were ruled out as significant factors. Thus, this study contributes to the understanding of the Red Skin Disease and may act as a hypothesis generator for future studies.

Keywords: Atlantic salmon; Baltic Sea; Red Skin Disease; biomarkers; ecotoxicology.

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Conflict of interest statement

All authors declare that they do not have any conflict of interest.

Figures

FIGURE 1
FIGURE 1
Overview over the seven parameter sets analysed in connection with gross external disease signs using redundancy analysis (RDA)
FIGURE 2
FIGURE 2
Redundancy analysis (RDA) of whole blood‐associated biomarkers. Correlation triplot shows the ordination of clinical signs (red dots marked with Hr: haemorrhages, UL: UDN‐like lesions, Er: other skin erosions and My: mycosis). Black arrows indicate the relation between whole blood‐associated biomarkers—haematocrit (HT), haemoglobin (Hb), glucose (Glu), neutrophil leucocytes (nWBC), monocyte/macrophage leucocytes (mWBC), proerythrocytes (iRBC) and erythroblast (bRBC)—and disease pattern. Coloured dots show fitted site scores (linear combinations of explanatory variables) of individual samples. The cosine of the angle between the black arrows and the red dotted lines indicate an approximated correlation. Sample size per site: Mörrumsån (n = 4), Torneälven (n = 15), Ume‐/Vindelälven (n = 22), Indalsälven (n = 0), Lagan (n = 12)
FIGURE 3
FIGURE 3
Redundancy analysis (RDA) of plasma‐associated biomarkers. Correlation triplot shows the ordination of clinical signs (red dots marked with Hr: haemorrhages, UL: UDN‐like lesions, Er: other skin erosions and My: mycosis). Black arrows indicate the relation between whole blood‐associated biomarkers—titre of the complement system (CH50), plasma pH and concentrations of potassium (K+), sodium (Na+), chloride (Cl−) and calcium (Ca2+), free levels of thyroid hormones T3 and T4 (fT3 and fT4)—and disease pattern. Coloured dots show fitted site scores (linear combinations of explanatory variables) of individual samples. The cosine of the angle between the black arrows and the red dotted lines indicate an approximated correlation. Sample size per site: Mörrumsån (n = 4), Torneälven (n = 15), Ume‐/Vindelälven (n = 22), Indalsälven (n = 13), Lagan (n = 12)
FIGURE 4
FIGURE 4
Redundancy analysis (RDA) of liver‐associated biomarkers. Correlation triplot shows the ordination of clinical signs (red dots marked with Hr: haemorrhages, UL: UDN‐like lesions, Er: other skin erosions and My: mycosis). Black arrows indicate the relation between whole blood‐associated biomarkers—catalase (CAT), glutathione reductase (GR), glutathione S‐transferases (GST), ratio between reduced and oxidized form of glutathione (GSH/GSSG), protein carbonyls (PC), free thiamine (fTh), thiamine monophosphate (TMP) and thiamine pyrophosphate (TPP)—and disease pattern. Coloured dots show fitted site scores (linear combinations of explanatory variables) of individual samples. The cosine of the angle between the black arrows and the red dotted lines indicate an approximated correlation. Sample size per site: Mörrumsån (n = 4), Torneälven (n = 13), Ume‐/Vindelälven (n = 20), Indalsälven (n = 0), Lagan (n = 12)
FIGURE 5
FIGURE 5
Redundancy analysis (RDA) of previously significant parameters. Correlation triplot shows the ordination of clinical signs (red dots marked with Hr: haemorrhages, UL: UDN‐like lesions, Er: other skin erosions and My: mycosis). Black arrows indicate the relation between selected parameters—glucose (Glu), neutrophil leucocytes (nWBC), monocyte/macrophage leucocytes (mWBC), titre of the complement system (CH50), plasma pH and concentrations of sodium (Na+) and chloride (Cl−), free levels of thyroid hormones T3 and T4 (fT3 and fT4), glutathione S‐transferases (GST) and free thiamine (fTh)—and disease pattern. Coloured dots show fitted site scores (linear combinations of explanatory variables) of individual samples. The cosine of the angle between the black arrows and the red dotted lines indicate an approximated correlation. Sample size per site: Mörrumsån (n = 4), Torneälven (n = 15), Ume‐/Vindelälven (n = 21), Indalsälven (n = 0), Lagan (n = 11)
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