Evidence map›Paper›PMID 40661263›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Polygenic scores for precision psychiatry: a study on the effect heterogeneity of antidepressants.

Ryunosuke Goto, Tatsuhiko Naito, Norbert Skokauskas, Kosuke Inoue

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

4 authors.

Ryunosuke GotoDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA.ORCID 0000-0002-4164-0990
Tatsuhiko NaitoNash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Norbert SkokauskasRegional Centre for Children and Youth Mental Health and Child Welfare - Central Norway, IPH, Norwegian University of Science and Technology, Trondheim, Norway.
Kosuke InoueDepartment of Social Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Funding

Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7M
Precision Medicine Initiative Cohort Program BiobankU24OD023121 · OD · MAYO CLINIC ROCHESTER · PI CEKANOVA, MARIA, CICEK, MINE · 2016 to 2024
$185.5M
Enhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7M
Adaptive Platform for Personalized EngagementU24OD023163 · OD · VIGNET, INC. · PI JAIN, PRADUMAN · 2017 to 2020
$102.6M
University of Arizona-Banner Health All of Us Research Program OT2OD026549 · OD · UNIVERSITY OF ARIZONA · PI MORENO, FRANCISCO A, REIMAN, ERIC MICHAEL · 2018 to 2023
$78.9M
California Precision Medicine Research Program ConsortiumOT2OD026552 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANTON-CULVER, HODA A, OHNO-MACHADO, LUCILA · 2018 to 2023
$73.4M
All of Us PennsylvaniaOT2OD026554 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E, VISWESWARAN, SHYAM · 2018 to 2023
$72.1M
New York City Consortium for Precision MedicineOT2OD026556 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BIER, LOUISE E, GHARAVI, ALI G · 2018 to 2023
$67.3M
SouthEast Enrollment Center (SEEC) OT2OD026551 · OD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, COLON, VIVIAN · 2018 to 2023
$62.8M
Southern All of Us NetworkOT2OD026548 · OD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI FOUAD, MONA N., KORF, BRUCE R · 2018 to 2023
$60.5M
Illinois Precision Medicine Consortium OT2OD026557 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI AHSAN, HABIBUL, ARGOS, MARIA · 2018 to 2023
$60.5M
The New England Precision Medicine Consortium of the All of Us Research ProgramOT2OD026553 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI CLARK, CHERYL RENEE, KARLSON, ELIZABETH W · 2018 to 2023
$58.8M
NIH HHS OT2 OD023205NIH HHS OT2 OD023206NIH HHS OT2 OD025276NIH HHS OT2 OD025277NIH HHS OT2 OD025315NIH HHS OT2 OD025337NIH HHS OT2 OD026548NIH HHS OT2 OD026549NIH HHS OT2 OD026550NIH HHS OT2 OD026551NIH HHS OT2 OD026552NIH HHS OT2 OD026553NIH HHS OT2 OD026554NIH HHS OT2 OD026555NIH HHS OT2 OD026556NIH HHS OT2 OD026557NIH HHS U24 OD023121NIH HHS U24 OD023163NIH HHS U24 OD023176NIH HHS U2C OD023196
6 · The paper itself

Abstract

Importance: Antidepressants are recommended as the initial choice of treatment for moderate and severe depression, but the choice of antidepressant class can be challenging, with the possibility of serious adverse events such as increased suicidality with antidepressant initiation. Objective: To evaluate the utility of polygenic scores in predicting heterogeneous effects of antidepressants on suicidal thoughts. Design: Using genetic and clinical data on both children and adults with major depressive disorder from the All of Us Research Program, we used a target trial emulation framework to evaluate the heterogeneous effects of antidepressants on suicidal thoughts across genetic characteristics. Setting: Longitudinal cohort from the All of Us Research Program. Participants: More than 7,000 patients, both children and adults, with major depressive disorder. Interventions: The initiation of selective serotonin reuptake inhibitors (SSRIs), compared to the initiation of serotonin and norepinephrine reuptake inhibitors (SNRIs) and bupropion. Main Outcomes and Measures: The effects of antidepressants on suicidal thoughts, as well as subgroup effects across polygenic scores (PGSs) of various psychiatric disorders. Results: Patients with higher PGS for psychiatric disorders, particularly for attention deficit-hyperactivity disorder (ADHD), were more likely than those with lower scores to experience suicidal thoughts with the initiation of SSRIs, relative to bupropion (hazard ratio 1.66, 95%CI, 1.30-2.12, for participants with ADHD PGS higher than median vs. hazard ratio 1.06, 95%CI, 0.81-1.38, for participants with ADHD PGS lower than median; P-for-interaction, 0.01). We observed a similar trend for schizophrenia, although the interaction was not statistically significant (hazard ratio 1.52, 95%CI, 1.19-1.93, for participants with schizophrenia PGS higher than median vs. hazard ratio 1.1.17, 95%CI, 0.89-1.53, for participants with ADHD PGS lower than median; P-for-interaction, 0.16). We did not observe differences in the effects of SSRIs relative to SNRIs across PGSs. Conclusions and Relevance: The genetic predisposition to psychiatric disorders may, at least partially, underlie the heterogeneity in the risk of suicidal thoughts with antidepressant use. In the personalized medicine framework, PGSs for various psychiatric disorders may help tailor antidepressants to each patient to avoid serious adverse effects such as suicidal thoughts.

Identifiers

PMID40661263
PMCPMC12258772

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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.