Evidence map›Paper›PMID 36711661›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Genetic liability to major psychiatric disorders contributes to multi-faceted quality of life outcomes in children and adults.

Yingjie Shi, Barbara Franke, Nina Roth Mota, Emma Sprooten

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Yingjie ShiDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Barbara FrankeDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Nina Roth MotaDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Emma SprootenDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Radboud University Nijmegen · NL

Funding

ABCD-USA Consortium: Coordinating CenterU24DA041147 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SANDRA A BROWN, TERRY L. JERNIGAN · 2015 to 2026
$54.7M
ABCD-USA Consortium: Data Analysis, Informatics and Resource CenterU24DA041123 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE · 2015 to 2026
$51.5M
Adolescent Substance Use Initiation: Disentangling neurocognitive risks from consequences using longitudinal and genetically-informed methodsU01DA041120 · NIDA · UNIVERSITY OF MINNESOTA · PI Monica Luciana, Sylia Wilson · 2015 to 2026
$34.5M
ABCD-USA Consortium: Research ProjectU01DA041089 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Joanna Jacobus, Susan F. Tapert · 2015 to 2026
$31.7M
Prospective Research Studies of Maturation (PRISM)- Research ProjectU01DA041134 · NIDA · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI ERIN MCGLADE, PERRY FRANKLIN RENSHAW · 2015 to 2026
$29.2M
ABCD-USA CONSORTIUM: RESEARCH PROJECTU01DA041048 · NIDA · CHILDREN'S HOSPITAL OF LOS ANGELES · PI Megan Marie Herting, ELIZABETH R SOWELL · 2015 to 2026
$28.7M
ABCD-USA Consortium: Research ProjectU01DA041106 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mary M Heitzeg, Chandra Sekhar Sripada · 2015 to 2026
$24.9M
FIU-ABCD: Pathways and Mechanisms to Addiction in the Latino Youth of South FloridaU01DA041156 · NIDA · FLORIDA INTERNATIONAL UNIVERSITY · PI Raul Gonzalez, Angela R Laird · 2015 to 2026
$22.8M
ABCD-USA Consortium: Research ProjectU01DA041148 · NIDA · OREGON HEALTH & SCIENCE UNIVERSITY · PI Damien A Fair, Rebekah S Huber · 2015 to 2026
$22.3M
ABCD-USA: NYC Research ProjectU01DA041174 · NIDA · YALE UNIVERSITY · PI Arielle Ryan Baskin-Sommers, Betty J Casey · 2015 to 2026
$19.7M
Adolescent Brain Cognitive Development (ABCD) Prospective Research in Studies of Maturation (PRISM) ConsortiumU01DA041117 · NIDA · UNIVERSITY OF MARYLAND BALTIMORE · PI LINDA CHANG, THOMAS M ERNST · 2015 to 2026
$19.5M
15/21 ABCD-USA Consortium: Research Project Site at LIBRU01DA050989 · NIDA · LAUREATE INSTITUTE FOR BRAIN RESEARCH · PI ROBIN L AUPPERLE, MARTIN P. PAULUS · 2020 to 2026
$14.7M
Medical Research Council MC_PC_17228NIDA NIH HHS U01 DA041022NIDA NIH HHS U01 DA041025NIDA NIH HHS U01 DA041028NIDA NIH HHS U01 DA041048NIDA NIH HHS U01 DA041089NIDA NIH HHS U01 DA041093NIDA NIH HHS U01 DA041106NIDA NIH HHS U01 DA041117NIDA NIH HHS U01 DA041120NIDA NIH HHS U01 DA041134NIDA NIH HHS U01 DA041148NIDA NIH HHS U01 DA041156NIDA NIH HHS U01 DA041174NIDA NIH HHS U01 DA050987NIDA NIH HHS U01 DA050988NIDA NIH HHS U01 DA050989NIDA NIH HHS U01 DA051016NIDA NIH HHS U01 DA051018NIDA NIH HHS U01 DA051037NIDA NIH HHS U01 DA051038NIDA NIH HHS U01 DA051039NIDA NIH HHS U24 DA041123NIDA NIH HHS U24 DA041147NIMH NIH HHS R01 MH124851Wellcome Trust
6 · The paper itself

Abstract

Importance: Psychiatric disorders can have an immense impact on socioeconomic, physical, and social-psychological facets of life. Psychiatric disorders are also highly heritable. Under a liability threshold model, an important question arises as to what extent genetic liability for psychiatric disorders relates to, and possibly impacts on, different aspects of quality of life in the general population. Objective: To characterize the link between psychiatric genetic liability and diverse aspects of quality of life in childhood and adulthood. Design setting and participants: We used data from two multi-site, population-based cohorts, i.e. preadolescent children in the USA enrolled at age 9-10 years from the Adolescent Brain Cognitive Development (ABCD) study (N=4,645) and white British adults between age 40-69 years from the UK Biobank (UKB) study (N=377,664). Due to the current limitations of our genetic methods, only data from unrelated individuals of European descent could be included. Main outcomes and measures: To derive robust measures capturing multiple domains of quality of life in each of the cohorts, we integrated an array of measurements of academic, economic, and physical status, as well as social well-being, in a second-level three-factor confirmatory factor analysis. The genetic liabilities to seven major psychiatric disorders were quantified by a set of polygenic scores (PGSs) derived from the largest genome-wide association studies to date, independent of the target cohorts, of major depressive disorder (MDD, N=142k-173k), anxiety disorders (ANX, N=22k-144k), attention-deficit/hyperactivity disorder (ADHD, N=226k), autism spectrum disorder (ASD, N=55k), schizophrenia (SCZ, N=130k), bipolar disorder (BIP, N=353k-414k), and cannabis use disorder (CUD, N=384k). Using general linear models we assessed associations between PGSs and the estimated latent factors, controlling for age, sex, site, genotyping batch, plate, and genetic ancestry. Results: In each cohort, three latent factors indexing distinct but correlated quality of life domains, (1) educational performance and cognition (Edu, in ABCD) / social economic status (SES, in UKB), (2) physical health (Hea), (3) adverse social experience (Adv, in ABCD) / social well-being (Soc, in UKB), were estimated with excellent model fit indices. In addition, a general factor was derived that captured the covariances between the three latent factors (QoL). In the ABCD cohort, ADHD-PGS was significantly associated with Edu (β = -0.13, t = -8.29, p = 1.53e-16), Adv (β = -0.09, t = -5.79, p = 7.81e-09), and general QoL (β = -0.14, t = -8.74, p = 3.37e-18) factors. In the UKB cohort, all examined disorder PGSs were significantly associated with the general QoL latent factor and at least one first-order subdomain, with ADHD-PGS (β = -0.06 ~ -0.10, t = -29.1 ~ -52.5, p < 5.91e-186) and MDD-PGS (β = -0.04 ~ -0.07, t = -23.8 ~ -36.3, p < 3.63e-125) showing the largest effects. Conclusions and relevance: The present study reveals an inverse relationship between psychiatric genetic liabilities and multiple quality of life metrics, with ADHD-associated genetic risk being the main contributor in both children and adults, and MDD additionally showing effects in adults. All effect sizes observed were small, as expected. Understanding potential real-world outcomes of quantitative measures of disorder-related genetic risks in the general population can provide a scientific foundation for societal intervention and policy-making processes, with profound implications for promoting a flourishing society.

Identifiers

PMID36711661
PMCPMC9882403
OpenAlexW4317242205

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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.