ArticleHuman genetics2009
Linkage and heritability analysis of migraine symptom groupings: a comparison of three different clustering methods on twin data.
Article in Human genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- An Integrative Migraine Polygenic Risk Score Is Associated with Age at Onset But Not Chronification.Journal of clinical medicine · 2024Article
- Classifying migraine subtypes and their characteristics by latent class analysis using data of a nation-wide population-based study.Scientific reports · 2021Article
- Article
- Article
- Bayesian latent trait modeling of migraine symptom data.Human genetics · 2009Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Migraine is a painful disorder for which the etiology remains obscure. Diagnosis is largely based on International Headache Society criteria. However, no feature occurs in all patients who meet these criteria, and no single symptom is required for diagnosis. Consequently, this definition may not accurately reflect the phenotypic heterogeneity or genetic basis of the disorder. Such phenotypic uncertainty is typical for complex genetic disorders and has encouraged interest in multivariate statistical methods for classifying disease phenotypes. We applied three popular statistical phenotyping methods-latent class analysis, grade of membership and grade of membership "fuzzy" clustering (Fanny)-to migraine symptom data, and compared heritability and genome-wide linkage results obtained using each approach. Our results demonstrate that different methodologies produce different clustering structures and non-negligible differences in subsequent analyses. We therefore urge caution in the use of any single approach and suggest that multiple phenotyping methods be used.
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Registered trials
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