Evidence map›Paper›PMID 25832296›Full record

ArticleGenetic epidemiology2015

Genetic analyses benefit from using less heterogeneous phenotypes: an illustration with the hospital anxiety and depression scale (HADS).

Charles A Laurin, Jouke-Jan Hottenga, Gonneke Willemsen, Dorret I Boomsma, Gitta H Lubke

Abstract read
In one paragraph

Article in Genetic epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 20% of its field
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

7 citing papers in PubMed, 15 citations in OpenAlex.

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  6. A powerful phenotype for gene-finding studies derived from trajectory analyses of symptoms of anxiety and depression between age seven and 18.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2016
    Article
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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 at 2 institutions in 3 countries.

Charles A LaurinDepartment of Psychology, University of Notre Dame, Notre Dame, Indiana, United States of America; Integrated Epidemiology Unit, School of Social and Community Medicine, University of Bristol, United Kingdom.
Jouke-Jan Hottenga
Gonneke Willemsen
Dorret I Boomsma
Gitta H Lubke
Vrije Universiteit Amsterdam · NLUniversity of Notre Dame · US

Funding

NIMH Center Repository Supporting Stem Cell ResearchU24MH068457 · NIMH · RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK · PI BRZUSTOWICZ, LINDA M, KNOWLES, JAMES A · 2003 to 2024
$213.8M
Integration of Genomics & Transcriptomics in Normal Twins & Major DepressionRC2MH089951 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SULLIVAN, PATRICK F · 2009 to 2010
$6.5M
Psychometric and Genetic Assessments of Substance UseR37DA018673 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI NEALE, MICHAEL CHURTON · 2005 to 2014
$3.7M
Psychometric and Genetic Assessments of Substance UseR01DA018673 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI NEALE, MICHAEL CHURTON · 2004 to 2019
$2.3M
Collaborative Study of Genetics of Dizygotic TwinningR01HD042157 · NICHD · QUEENSLAND INSTITUTE OF MEDICAL RESEARCH · PI MONTGOMERY, GRANT W · 2002 to 2006
$2.0M
Major Depression: Stage 1 Genomewide Association in Population-Based SamplesR01MH081802 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SULLIVAN, PATRICK F · 2007 to 2007
$138k
European Research Council 230374NICHD NIH HHS R01 HD042157NICHD NIH HHS R01HD042157-01A1NIDA NIH HHS R01 DA018673NIDA NIH HHS R37 DA018673NIMH NIH HHS 1RC2 MH089951NIMH NIH HHS MH081802NIMH NIH HHS R01 MH081802NIMH NIH HHS RC2 MH089951NIMH NIH HHS U24 MH068457NIMH NIH HHS U24 MH068457-06PHS HHS NIDA-DA018673
6 · The paper itself

Abstract

Phenotypic heterogeneity of depression has been cited as one of the causes of the limited success to detect genetic variants in genome-wide studies. The 7-item Hospital Anxiety and Depression Scale (HADS-D) was developed to detect depression in individuals with physical health problems. An initial psychometric analysis showed that a short version ("HADS-4") is less heterogeneous and hence more reliable than the full scale, and correlates equally strong with a DSM-oriented depression scale. We compared the HADS-D and the HADS-4 to assess the benefits of using less heterogeneous phenotype measures in genetic analyses. We compared HADS-D and HADS-4 in three separate analyses: (1) twin- and family-based heritability estimation, (2) SNP-based heritability estimation using the software GCTA, and (3) a genome-wide association study (GWAS). The twin study resulted in heritability estimates between 18% and 25%, with additive genetic variance being the largest component. There was also evidence for assortative mating and a dominance component of genetic variance, with HADS-4 having slightly lower estimates of assortment. Importantly, when estimating heritability from SNPs, the HADS-D did not show a significant genetic variance component, while for the HADS-4, a statistically significant amount of heritability was estimated. Moreover, the HADS-4 had substantially more SNPs with small P-values in the GWAS analysis than did the HADS-D. Our results underline the benefits of using more homogeneous phenotypes in psychiatric genetic analyses. Homogeneity can be increased by focusing on core symptoms of disorders, thus reducing the noise in aggregate phenotypes caused by substantially different symptom profiles.

Indexed as

Genome-Wide Association StudyPsychiatric Status Rating ScalesAlgorithmsAnxiety DisordersDepressive DisorderFamilyFemaleGenetic TestingHumansMaleMiddle AgedPhenotypePolymorphism, Single NucleotidePsychometricsTwin Studies as TopicdepressionGCTAGWASHADSheterogeneityreliability

Identifiers

PMID25832296
PMCPMC4406831
OpenAlexW2063114183

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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 OpenQuestion graph.