Evidence map›Paper›PMID 41746958›Full record

ArticlePloS one2026

Revisiting Minamata disease through computational phenotypic similarity analysis.

Edoardo Marchi, Paolo Boldi, Elena Casiraghi, Stefano Zapperi, Caterina A M La Porta

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Edoardo MarchiDepartment of Environmental Science and Policy, Università degli Studi di Milano, Milan, Italy.ORCID https://orcid.org/0009-0000-0917-6190
Paolo BoldiCenter for Complexity and Biosystems, University of Milan, Milan, Italy.ORCID https://orcid.org/0000-0002-8297-6255
Elena CasiraghiDepartment of Computer Science, Università degli Studi di Milano, Milan, Italy.ORCID https://orcid.org/0000-0003-2024-7572
Stefano ZapperiCenter for Complexity and Biosystems, University of Milan, Milan, Italy.ORCID https://orcid.org/0000-0001-5692-5465
Caterina A M La PortaDepartment of Environmental Science and Policy, Università degli Studi di Milano, Milan, Italy.ORCID https://orcid.org/0000-0002-3010-8966

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Minamata disease, a severe neurological disorder caused by methylmercury exposure in 1950s Japan, is historically recognized for its profound impact on environmental health awareness. However, its phenotypic complexity and potential overlap with other neurological disorders have not been systematically assessed in a modern computational framework. In this study, we adopt a network approach to reinterpret Minamata disease within a broader disease similarity landscape. We mapped clinical symptoms from an extensive epidemiological survey of 269 Minamata patients to standardized Human Phenotype Ontology (HPO) terms, constructing a comprehensive phenotypic profile. Using network-based and computational similarity measures-Jaccard Index, ontology-informed metrics (Resnik and GraphIC), and information retrieval techniques (TF-IDF with query expansion), we compared this profile to over 12,000 diseases. Our results consistently identified strong phenotypic ties between Minamata disease and several movement and neurodegenerative disorders, including cyanide-induced parkinsonism and progressive supranuclear palsy. A weighted rank aggregation across methods revealed a robust consensus network of diseases with overlapping symptomatology, underscoring the systemic nature of these complex neurological disorders. Our study highlights the utility of integrating historical epidemiological data with contemporary network tools to reveal novel associations between environmental exposures and systemic pathophysiological responses. Our findings provide a blueprint for exploring environmentally triggered disease mechanisms and their broader implications for network-based understanding of human disease.

Identifiers

PMID41746958
PMCPMC12944806

What Socratic holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.