Data · dataset · 2025
Association of hypothyroidism with sepsis: a two-sample Mendelian randomization study
Listed in ScienceDB
Objective Exploring the causal relationship between hypothyroidism and sepsis from the perspective of genetics.
Description
Methods
Based on the published genome-wide association study, two sample Mendelian randomization method was used, with hypothyroidism as the exposure factor and sepsis as the outcome factor, single nucleotide polymorphisms (SNPs) strongly associated with hypothyroidism (p<5e-8) were selected as instrumental variables (IV), and linkage disequilibrium was removed. Inverse variance weighted (IVW) was used as the main analysis method, and MR-egger, weighted median, simple mode, weighted mode, Bayesian Weighted Mendelian Randomization (BWMR), Constrained Maximum Likelihood and Model Averaging (CML MA) were used as supplements to evaluate the causal relationship between hypothyroidism and sepsis.
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For sensitivity analysis, MR-Egger regression intercept and MR-PRESSO global test were used to test for pleiotropy, and Cochran-Q test was used to assess heterogeneity. Finally, reverse Mendelian randomization analysis was performed to prove whether there was reverse causality.Results IVW method found that hypothyroid patients had an increased risk of sepsis (β = 0.05, P = 0.008, or = 1.05, 95% CI = 1.01-1.09), BWMR and cML-MA also showed that the results were statistically significant (p<0.05), while the other methods showed no statistical significance (p>0.05).
The direction of effect value (β) of all methods was the same. The results of pleiotropy analysis and heterogeneity analysis showed that the results were robust (p>0.05). Reverse Mendelian randomization verifies that there is no reverse causal relationship between the two.Conclusion Hypothyroidism is causally related to sepsis, and hypothyroidism increases the risk of sepsis.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00217.11071 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Bioinformatics and computational biology 68%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00217.11071 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3102 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (68%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |