Evidence mapPaperPMID 40822600Full record

ArticleJournal of mood and anxiety disorders2025

Implications of the choice of method to identify major depressive disorder in large research cohorts.

Jorge A Sanchez-Ruiz, Nicolas A Nuñez, Gregory D Jenkins, Brandon J Coombes, Lauren A Lepow, Braja Gopal Patra, Ardesheer Talati, Mark Olfson, J John Mann, Myrna M Weissman and 4 more

Abstract read
In one paragraph

Article in Journal of mood and anxiety disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

14 authors.

Jorge A Sanchez-RuizDepartment of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
Nicolas A NuñezDepartment of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
Gregory D JenkinsDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Brandon J CoombesDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Lauren A LepowDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Braja Gopal PatraDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
Ardesheer TalatiDepartment of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, NY, USA.
Mark OlfsonDepartment of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, NY, USA.
J John MannDepartment of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, NY, USA.
Myrna M WeissmanDepartment of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, NY, USA.
Jyotishman PathakDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
Alexander CharneyDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Euijung RyuDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Joanna M BiernackaDepartment of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.

Funding

6/7 PsycheMERGE: Advancing Precision PsychiatryR01MH137213 · MAYO CLINIC ROCHESTER · 2025 to 2025
$442k
2/4: Leveraging EHR-linked biobanks for deep phenotyping, polygenic risk score modeling, and outcomes analysis in psychiatric disordersR01MH121924 · NIMH · MAYO CLINIC ROCHESTER · PI Joanna M Biernacka · 2023 to 2023
$405k
Training the next generation of clinical neuroscientistsT32MH122394 · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2025 to 2025
$392k
NIMH NIH HHS R01 MH121924NIMH NIH HHS R01 MH137213NIMH NIH HHS T32 MH122394
6 · The paper itself

Abstract

Background: Clinical heterogeneity and variations in methods to identify major depressive disorder (MDD) across studies compromise replicability of research findings. This study evaluated potential implications of different MDD case definitions in a large biobank cohort. Methods: Among Mayo Clinic Biobank participants, MDD was identified using two methods: self-report MDD in a participant questionnaire (PQ-MDD) and MDD ICD codes in the electronic health record (EHR-MDD). We examined agreement between these definitions and evaluated relationships between case agreement and participant characteristics, including MDD polygenic risk scores (PRS). Finally, we evaluated associations between different MDD case/control definitions and participant characteristics known to be related to MDD. Results: Among 55,656 participants, 23 % were identified as PQ-MDD cases and 17 % as EHR-MDD cases, with 85 % overall agreement (61 % case agreement) between these definitions. Among participants identified as MDD cases by one method, older and male patients, and those with lower measures of morbidity at enrollment, were less likely to be identified as cases by the other method. The strength of the associations between different MDD case/control definitions and participant characteristics varied depending on whether MDD definitions used the same source of information (i.e., EHR-only, self-report only)-resulting in stronger associations-versus different sources of information (i.e., one from EHR, one from self-report)-resulting in weaker associations. Conclusion: Our results demonstrate how the methods used to identify patients with history of MDD can affect sample characteristics and risk factor associations, highlighting the importance of considering phenotype ascertainment in the interpretation of research results.

Indexed as

Depressive disorderElectronic health recordsGenetic risk scoreMajorMental healthSelf report

Identifiers

PMID40822600
PMCPMC12351683

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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.