Atlantic salmon (Salmo salar) aquaculture suffers substantial losses due to infectious and non-infectious diseases. However, the ecological basis of gut microbiome dysbiosis remains poorly understood across geographically distinct production systems. A key unresolved question is whether dysbiosis results from the restructuring of resident microbial communities or from the introduction or acquisition of exogenous microorganisms. To address this, a multi-country pooled cross-study reanalysis of publicly available 16S rRNA gut microbiome datasets from Ireland (V1V2, n = 234), Norway (V1V3, n = 4), Chile (V4, n = 70), and China (V4, n = 12) was conducted, comprising 320 samples after quality check and taxonomic filtering. An integrative analytical framework was applied, combining compositional microbiome analysis, microbial source tracking, and machine learning approaches to identify generalized disease-associated dysbiosis signatures in a pooled dataset comprising geographically distinct salmon populations. The analysis found strong between-cohort structure in microbiome composition, whereas disease status produced smaller but significant compositional differences without clear visual separation. Alpha diversity was not significantly linked to disease condition, although ANCOM-BC2 analysis identified 48 genera with significantly altered abundances between healthy and diseased fish. In the pooled dataset, healthy fish showed higher abundance of genera such as Mycoplasma, Oleispira, Aliivibrio, Psychrobium, and Cobetia. In contrast, diseased individuals were enriched in Pseudomonas, Prevotella, Massilia, Chryseobacterium, and multiple genera affiliated with Flavobacteriaceae. Using Random Forest classification, an AUC-ROC of 0.819 was achieved, with Oleispira the strongest health-associated genus in both the Shapley Additive Explanations (SHAP) ranking and the ANCOM-BC2 analysis; this association derives from the Irish cohort, whereas Mycoplasma, Pseudomonas and Aliivibrio retained direction and significance when the Irish cohort was excluded. Under leave-one-study-out validation, accuracy was 66.2% for Ireland, 58.3% for China, 50.0% for Norway and 35.7% for Chile. Classifier performance, therefore, showed limited cross-cohort transferability, and the pooled estimate should not be interpreted as a diagnostic accuracy estimate. Microbial source tracking indicated substantial compositional overlap between diseased fish microbiomes and the selected healthy reference pool, with a mean healthy source attribution of 93.5%; this does not exclude acquisition of organisms from external sources. Overall, these findings suggest that gut dysbiosis in Atlantic salmon is consistent with compositional reconfiguration of a shared genus pool, although this pattern does not establish microbial provenance.