Evidence map›Paper›PMID 39667704›Full record

ArticleJournal of affective disorders2025

Heritability, phenotypic, and genetic correlations across dimensional and categorical models of bipolar disorder in a family sample.

Alejandro Arbona-Lampaya, Heejong Sung, Alexander D'Amico, Emma E M Knowles, Emily K Besançon, Ally Freifeld, Ley Lacbawan, Fabiana Lopes, Layla Kassem, Antonio E Nardi and 1 more

Abstract read
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Article in Journal of affective disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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.

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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Alejandro Arbona-LampayaIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA; School of Medicine, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico. Electronic address: alejandro.arbona@upr.edu.
Heejong SungIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Alexander D'AmicoIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Emma E M KnowlesDepartment of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Emily K BesançonIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Ally FreifeldIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Ley LacbawanIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Fabiana LopesIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Layla KassemIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Antonio E NardiInstitute of Psychiatry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
Francis J McMahonIntramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA. Electronic address: mcmahonf@mail.nih.gov.

Funding

Identification of Genes Involved in Major Mood DisordersZIAMH002843 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI MCMAHON, FRANCIS J · 2009 to 2025
$24.5M
A Collaborative Genomic Study of Bipolar DisorderZ01MH002842 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI MCMAHON, FRANCIS J · 2004 to 2008
$1.2M
Intramural NIH HHS Z01 MH002842Intramural NIH HHS ZIA MH002843
6 · The paper itself

Abstract

backgroundBipolar disorder (BD) presents with a wide range of symptoms that vary among relatives, casting doubt on categorical illness models. To address this uncertainty, we investigated the heritability and genetic relationships between categorical and dimensional models of BD in a family sample.

methodsThis retrospective study included participants (n = 397 Females, n = 329 Males, mean age 47 yr) in the Amish-Mennonite Bipolar Genetics (AMBiGen) study from North and South America that were assigned categorical mood disorder diagnoses ("narrow" or "broad") by structured psychiatric interview and completed the Mood Disorder Questionnaire (MDQ), which assesses lifetime history of manic symptoms and associated impairment. MDQ-dimensions were analyzed by Principal Component Analysis (PCA). Heritability and genetic overlaps between categorical diagnoses and MDQ-dimensions were estimated with SOLAR-ECLIPSE within 432 genotyped participants.

resultsIndividuals diagnosed with BD (n = 124) endorsed more MDQ items (61 %) than those with other mood disorders (26 %) or with no mood disorder (9 %), as expected. PCA suggested a three-component model for the MDQ, capturing 60 % of the variance. Heritability of the MDQ and its principal components was significant but modest (20-30 %, p < 0.001). Genetic correlations between MDQ measures and categorical diagnoses (ρG = 0.62-1.0; p < 0.001) were stronger than phenotypic correlations (ρP = 0.11-0.58; p < 0.001). LIMITATIONS: Recruitment through probands with BD resulted in increased prevalence of BD in this sample, limiting generalizability. Unavailable genetic data reduced sample size for some analyses.

conclusionFindings support a genetic continuity between dimensional and categorical models of BD and suggest that the MDQ is a useful phenotype measure for genetic studies of BD.

Indexed as

Bipolar DisorderPhenotypeAdultFemaleGenetic Predisposition to DiseaseGenotypeHumansMaleMiddle AgedPrincipal Component AnalysisPsychiatric Status Rating ScalesRetrospective StudiesSurveys and QuestionnairesBipolar DisorderGenetic correlationHeritabilityMood Disorder QuestionnaireMood disordersPrincipal Component Analysis

Identifiers

PMID39667704
PMCPMC12633847

What Socratic holds

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LicenceCC BY-NC-ND
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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.