Evidence map›Paper›PMID 36685498›Full record

ArticleFrontiers in immunology2022

Depressive symptoms predict longitudinal changes of chronic inflammation at the transition to adulthood.

Shuang Zhai, Yang Qu, Dan Zhang, Tingting Li, Yang Xie, Xiaoyan Wu, Liwei Zou, Yajuan Yang, Fangbiao Tao, Shuman Tao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Observational
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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

10 authors at 3 institutions in 1 country.

Shuang ZhaiDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Yang QuDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Dan ZhangDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Tingting LiDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Yang XieDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Xiaoyan WuDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Liwei ZouKey Laboratory of Population Health Across Life Cycle, Ministry of Education of the People's Republic of China, Hefei, China.
Yajuan YangKey Laboratory of Population Health Across Life Cycle, Ministry of Education of the People's Republic of China, Hefei, China.
Fangbiao TaoDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Shuman TaoKey Laboratory of Population Health Across Life Cycle, Ministry of Education of the People's Republic of China, Hefei, China.
Anhui Medical University · CNMinistry of Education of the People's Republic of China · CNSecond Affiliated Hospital of Anhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inflammation is closely related to poor mental and physical health, including depressive symptoms and its specific symptoms. To reveal the linear and nonlinear relationships between depressive symptoms and chronic inflammation levels, and perform further analysis of the associations between symptom-specificity of depressive symptoms and inflammation among young adults by using a prospective design. Methods: In this longitudinal study, we examined college students recruited from two universities in China, who were examined at baseline and 2-years follow-up. Depressive symptoms were measured by applying the Patient Health Questionnaire 9 (PHQ-9) at baseline. Plasma levels of four inflammatory biomarkers, including interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and C reactive protein (CRP) were assayed at baseline and 2-year follow-up. In addition to the conventional generalized linear models, as well as restricted cubic splines were innovatively used to analyze the cross-sectional and longitudinal nonlinear relationships between depressive symptoms and inflammatory biomarkers. Results: Generalized linear model analysis revealed that there were no statistical associations between depressive symptoms and any inflammatory biomarker levels. The results of the restricted cubic spline demonstrated a U-shaped nonlinear association between depressive symptoms and ΔIL-1β or ΔTNF-α (changes in baseline and 2-year follow-up), but these associations disappeared after adjusting the confounders. Symptom-specificity of depressive symptoms such as sleeping problems and suicidal ideation were associated with lower IL-1β at baseline or changes in IL-1β levels. Sleeping problems and psychomotor changes at baseline were associated with higher CRP at 2-year follow-up. Suicidal ideation at baseline was associated with changes in TNF-α levels. Conclusion: Our findings suggested that symptom-specificity of depressive symptoms was associated with inflammation during a 2-year follow-up at the transition to adulthood. Simultaneously, more research is warranted to seek the directionality of depressive symptoms and chronic inflammation.

Indexed as

DepressionSleep Wake DisordersBiomarkersC-Reactive ProteinCross-Sectional StudiesHumansInflammationLongitudinal StudiesTumor Necrosis Factor-alphaYoung AdultBiomarkersC-Reactive ProteinTumor Necrosis Factor-alphaDepressive symptomsdose-response relationshipfollow-up studyinflammatory biomarkersyoung adults

Identifiers

PMID36685498
PMCPMC9846044
OpenAlexW4313584907

What OpenQuestion holds

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LicenceCC BY
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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.