| Title: | SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice |
| Journal: | Research |
| Published: | 1 Jan 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38434247/ |
| DOI: | https://doi.org/10.34133/research.0269 |
Publication 10903
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Abstract
Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.</p>
15 Authors
- Xiujuan Du
- Yuhua Yan
- Juehua Yu
- Tailin Zhu
- Chu-Chung Huang
- Lingli Zhang
- Xingyue Shan
- Ren Li
- Yuan Dai
- Hui Lv
- Xiao-Yong Zhang
- Jianfeng Feng
- Wei-Guang Li
- Qiang Luo
- Fei Li
1 Application
| Application ID | Title |
|---|---|
| 19542 | Identifying multi-level biomarkers and disease mechanisms for major mental disorders |
Enabling scientific discoveries that improve human health