Evidence map›Paper›PMID 39849528›Full record

ArticleBMC medicine2025

Bridging animal models and humans: neuroimaging as intermediate phenotypes linking genetic or stress factors to anhedonia.

Huiling Guo, Yao Xiao, Shuai Dong, Jingyu Yang, Pengfei Zhao, Tongtong Zhao, Aoling Cai, Lili Tang, Juan Liu, Hui Wang and 16 more

Abstract read
In one paragraph

Article in BMC medicine, 2025. 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
–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

5 citing papers in PubMed.

  1. Review
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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

26 authors.

Huiling Guo *Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Yao Xiao *Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Shuai DongEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Jingyu YangEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Pengfei ZhaoEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Tongtong ZhaoEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Aoling CaiEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Lili TangEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Juan LiuEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Hui WangHenan Key Laboratory of Immunology and Targeted Drugs, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China.
Ruifang HuaHenan Key Laboratory of Immunology and Targeted Drugs, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China.
Rongxun LiuEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Yange WeiEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China.
Dandan SunDepartment of Cardiac Function, The People's Hospital of China Medical University and the People's Hospital of Liaoning Province, Shenyang, China.
Zhongchun LiuDepartment of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Mingrui XiaState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Yong HeState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Yankun WuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China.
Tianmei SiPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China.
Fay Y WomerDepartment of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
Fuqiang XuKey Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.
Yanqing TangDepartment of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, China.
Jie WangSongjiang Research Institute, Songjiang Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. jie.wang@wipm.ac.cn.
Weixiong ZhangDepartment of Health Technology and Informatics, Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China. weixiong.zhang@polyu.edu.hk.
Xizhe ZhangEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China. zhangxizhe@njmu.edu.cn.
Fei WangEarly Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Street, Nanjing, China. fei.wang@yale.edu.

Funding

China Postdoctoral Science Foundation 2021M691643Hong Kong Health and Medical Research Fund 10211696Hong Kong RGC Strategic Target Grant STG1/M-501/23-NJiangsu Provincial Key Research and Development Program BE2021617National Key Research and Development Program 2022YFC2405603National Natural Science Foundation of China 21921004National Natural Science Foundation of China 62176129National Natural Science Foundation of China 82301689National Natural Science Foundation of China-Guangdong Joint Fund U20A6005
6 · The paper itself

Abstract

backgroundIntermediate phenotypes, such as characteristic neuroimaging patterns, offer unique insights into the genetic and stress-related underpinnings of neuropsychiatric disorders like depression. This study aimed to identify neuroimaging intermediate phenotypes associated with depression, bridging etiological factors to behavioral manifestations and connecting insights from animal models to diverse clinical populations.

methodsWe analyzed datasets from both rodents and humans. The rodent studies included a genetic model (P11 knockout) and an environmental stress model (chronic unpredictable mild stress), while the human data comprised 748 participants from three cohorts. Using the amplitude of low-frequency fluctuations, we identified neuroimaging patterns in rodent models. We then applied a machine-learning approach to cluster neuroimaging subtypes of depression. To assess the genetic predispositions and stress-related changes associated with these subtypes, we analyzed genotype and metabolite data. Linear regression was employed to determine which neuroimaging features predicted core depression symptoms across species.

resultsThe genetic and environmental stress models exhibited distinct neuroimaging patterns in subcortical and sensorimotor regions. Consistent patterns emerged in two neuroimaging subtypes identified across three independent depressed cohorts. The subtype resembling P11 knockout demonstrated higher genetic susceptibility, with enriched expression of risk genes in brain tissues and abnormal metabolites linked to tryptophan metabolism. In contrast, the stress animal-like subtype did not show changes in genetic risk scores but exhibited enriched risk gene expression in somatic and endocrine tissues, along with mitochondrial dysfunction in the antioxidant stress system. Notably, these distinct subcortical-sensorimotor neuroimaging patterns predicted anhedonia, a core symptom of depression, in both rodent models and depressed subtypes.

conclusionsThis cross-species validation suggests that these neuroimaging patterns may serve as robust intermediate phenotypes, linking etiology to anhedonia and facilitating the translation of findings from animal models to humans with depression and other psychiatric disorders.

Indexed as

AnhedoniaBrainDepressionNeuroimagingStress, PsychologicalAdultAnimalsDisease Models, AnimalFemaleGenetic Predisposition to DiseaseHumansMachine LearningMagnetic Resonance ImagingMaleMiceMiddle AgedAnimalCross-speciesDepressionIntermediate phenotypesNeuroimagingSubtypes

Identifiers

PMID39849528
PMCPMC11755933

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.