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Background <p>Bipolar disorder (BD) is a severe mental illness characterized by seasonal episodes, yet its metabolic basis remains unclear.</p> Methods <p>This study utilized targeted metabolomics to investigate seasonal metabolic changes. Serum samples were collected from 9 BD patients And 9 matched healthy controls (HCs) at six time points: 15 days before, on, And 15 days after both the spring and autumn equinoxes. All samples were analyzed using the same platform for consistency.</p> Results <p>In the autumn phase, repeated-measures Analysis identified 15 metabolites in HCs And 38 in BD with time effects, And 111 showed group-by-time interactions; none remained significant after false discovery rate (FDR) correction. In contrast, Analysis across the spring And autumn revealed significant time effects in 277 metabolites in HCs And 263 in BD, with 16 triacylglycerols showing significant interactions (FDR-<i>p</i> &lt; 0.05). Group differences peaked around the autumn equinox, with opposite trends observed. Amino acids such as glutamine, lysine, histidine, and asymmetric dimethylarginine continuously increased from spring to autumn in both groups. These seasonal variations in BD metabolites from spring to autumn were mainly linked to the biosynthetic pathways of phenylalanine, tyrosine, and tryptophan.</p> Conclusion <p>These findings indicate a seasonal modulation of serum metabolite profiles in individuals with BD, which may underlie or reflect mood-related changes. However, causal relationships and mechanistic pathways require further validation.</p>

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Investigating seasonal metabolic variations in bipolar disorder: a targeted metabolomics study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月7日

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  • Xue Li,
  • Xinzi Liu,
  • Ziyan Li,
  • Sitong Feng,
  • Sisi Zheng,
  • Hongxiao Jia,
  • Dongqing Yin

摘要

Background

Bipolar disorder (BD) is a severe mental illness characterized by seasonal episodes, yet its metabolic basis remains unclear.

Methods

This study utilized targeted metabolomics to investigate seasonal metabolic changes. Serum samples were collected from 9 BD patients And 9 matched healthy controls (HCs) at six time points: 15 days before, on, And 15 days after both the spring and autumn equinoxes. All samples were analyzed using the same platform for consistency.

Results

In the autumn phase, repeated-measures Analysis identified 15 metabolites in HCs And 38 in BD with time effects, And 111 showed group-by-time interactions; none remained significant after false discovery rate (FDR) correction. In contrast, Analysis across the spring And autumn revealed significant time effects in 277 metabolites in HCs And 263 in BD, with 16 triacylglycerols showing significant interactions (FDR-p < 0.05). Group differences peaked around the autumn equinox, with opposite trends observed. Amino acids such as glutamine, lysine, histidine, and asymmetric dimethylarginine continuously increased from spring to autumn in both groups. These seasonal variations in BD metabolites from spring to autumn were mainly linked to the biosynthetic pathways of phenylalanine, tyrosine, and tryptophan.

Conclusion

These findings indicate a seasonal modulation of serum metabolite profiles in individuals with BD, which may underlie or reflect mood-related changes. However, causal relationships and mechanistic pathways require further validation.