Evidence map›Paper›PMID 42768146›Full record

ArticleMolecular psychiatry2026

A thioredoxin-Serinc2-lipid signaling axis modulates mood-related behaviors in mice.

Chong-Lei Fu, Ying-Han Wang, Ya-Ni Zhang, Hong-Zuo Liu, Si-Yao Lu, Xin-Yu She, Dan Li, Bo-Cheng Dong, Xi Jiang, Zhen-Liang Yuan and 4 more

Abstract read
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In one paragraph

Article in Molecular psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

14 authors.

Chong-Lei Fu *State Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China. fuchonglei@163.com.ORCID http://orcid.org/0000-0002-1082-2783
Ying-Han Wang *State Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China.ORCID http://orcid.org/0000-0003-1652-7192
Ya-Ni Zhang *State Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Hong-Zuo LiuInstitute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China.ORCID http://orcid.org/0009-0004-2077-8829
Si-Yao LuJiangsu Key Laboratory of Language and Cognitive Neuroscience, School of Linguistic Sciences and Arts, Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, 221009, China.
Xin-Yu SheState Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Dan LiState Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Bo-Cheng DongState Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Xi JiangState Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Zhen-Liang YuanState Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Li-Lo GengJiangsu Key Laboratory of Language and Cognitive Neuroscience, School of Linguistic Sciences and Arts, Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, 221009, China.
Yi-Ming YangJiangsu Key Laboratory of Language and Cognitive Neuroscience, School of Linguistic Sciences and Arts, Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, 221009, China. yangym@jsnu.edu.cn.
Ke-Bing YangBeijing Huilongguan Hospital, Capital Medical University, Peking University Huilongguan Clinical Medical School, Beijing, 100096, China. 13910032541@163.com.
Jun YaoState Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing, 100084, China. jyao@mail.tsinghua.edu.cn.ORCID http://orcid.org/0000-0002-4916-3412

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32541061, 32371008
6 · The paper itself

Abstract

Bipolar disorder (BD) shows strong heritability and distinct symptomatic subtypes. However, the molecular basis underlying subtype-specific features remains poorly understood. Here, we identified Serinc2, a BD susceptibility gene encoding a L-serine transporter that regulates membrane lipid synthesis, as a regulator of mood-related behavioral phenotypes. Using patient plasma samples, BD iPSC-derived forebrain organoids, and Serinc2 knockout/overexpression mouse models, we found that Serinc2 expression was increased in bipolar I (BDI) but decreased in bipolar II (BDII); bi-directional manipulation of Serinc2 induced opposite changes in synaptic transmission and depression-related behaviors, accomplied by alterations in PS/SM-dependent redistribution of NMDAR subunits in postsynaptic membranes. Mechanistically, we found that thioredoxin (Txn) bound to the Serinc2 regulatory region and negatively regulate its transcription, and that differential chromatin accessibility of Txn contributed to subtype-associated expression patterns. Together, our results demonstrated a Txn-Serinc2-lipid signaling axis that linked membrane lipid composition to synaptic function and mood-related behaviors, and indicated a potential molecular framework contributing to subtype-specific features of BD.

Identifiers

PMID42768146

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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.