Evidence map›Paper›PMID 31278308›Full record

ArticleScientific reports2019

The UKB envirome of depression: from interactions to synergistic effects.

Gabor Hullam, Peter Antal, Peter Petschner, Xenia Gonda, Gyorgy Bagdy, Bill Deakin, Gabriella Juhasz

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

7 authors.

Gabor HullamDepartment of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, H-1117, Hungary.
Peter AntalDepartment of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, H-1117, Hungary.ORCID http://orcid.org/0000-0002-4370-2198
Peter PetschnerMTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, H-1089, Hungary.ORCID http://orcid.org/0000-0002-3198-858X
Xenia GondaMTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, H-1089, Hungary.ORCID http://orcid.org/0000-0001-9015-4203
Gyorgy BagdyMTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, H-1089, Hungary.
Bill DeakinNeuroscience and Psychiatry Unit, Division of Neuroscience and Experimental Psychology, University of Manchester and Manchester Academic Health Sciences Centre, Manchester, M13 9PL, UK.ORCID http://orcid.org/0000-0002-2750-962X
Gabriella JuhaszDepartment of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, H-1089, Hungary. juhasz.gabriella@pharma.semmelweis-univ.hu.ORCID http://orcid.org/0000-0002-5975-4267

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major depressive disorder is a result of the complex interplay between a large number of environmental and genetic factors but the comprehensive analysis of contributing environmental factors is still an open challenge. The primary aim of this work was to create a Bayesian dependency map of environmental factors of depression, including life stress, social and lifestyle factors, using the UK Biobank data to determine direct dependencies and to characterize mediating or interacting effects of other mental health, metabolic or pain conditions. As a complementary approach, we also investigated the non-linear, synergistic multi-factorial risk of the UKB envirome on depression using deep neural network architectures. Our results showed that a surprisingly small number of core factors mediate the effects of the envirome on lifetime depression: neuroticism, current depressive symptoms, parental depression, body fat, while life stress and household income have weak direct effects. Current depressive symptom showed strong or moderate direct relationships with life stress, pain conditions, falls, age, insomnia, weight change, satisfaction, confiding in someone, exercise, sports and Townsend index. In conclusion, the majority of envirome exerts their effects in a dynamic network via transitive, interactive and synergistic relationships explaining why environmental effects may be obscured in studies which consider them individually.

Indexed as

Bayes TheoremBiological Specimen BanksFemaleGene-Environment InteractionHumansLife StyleMajor Depressive DisorderMaleMultilevel AnalysisNeural Networks, ComputerRisk AssessmentUnited Kingdom

Identifiers

PMID31278308
PMCPMC6611783

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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 OpenQuestion graph.