Wang Yu-Jia, Zhou Zairen, Li Yu-Zhu, Kang Ju-Jiao, Yu Jin-Tai, Feng Jian-Feng, Cheng Wei, Pan Guoqing, You Jia, Wang Linbo
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
Commun Med (Lond). 2025 Jun 19;5(1):239. doi: 10.1038/s43856-025-00957-w.
Understanding the temporal trends of blood-based biomarkers and their associations with brain structure is crucial for early detection and intervention in psychiatric disorders. This study aimed to explore these trends in the decade before and after diagnosis, along with the cross-sectional relationships with brain structures.
Utilizing UK Biobank data, we conducted a nested case-control analysis of individuals aged 40-69 years diagnosed with anxiety (n = 27,216), bipolar disorder (n = 1325), depression (n = 36,570), or schizophrenia (n = 1478) within 10 years of baseline. We used multivariable linear regression to analyze temporal trends and brain structure associations for 31 blood cell counts, 28 biochemistry markers, and 168 serum metabolites.
Here we show that compared to controls, significant temporal divergence is observed in 39, 6, 55, and 12 blood-based markers for anxiety, bipolar disorder, depression, and schizophrenia, respectively. Common biomarkers like cystatin C, red blood cells, hemoglobin, hematocrit, and total bilirubin are identified. Biomarkers cluster into groups with either linear or non-linear trends. Among the linearly changing biomarkers, some have a widening difference from controls while others have a narrowing one. For example, in the case of depression, HDL-TG demonstrates an increasing disparity over time, while cholesterol exhibits a decreasing trend. Non-linear clusters often show reversals around diagnosis, indicating potential treatment effects. Differential associations are found between biomarkers and brain regions, including the orbitofrontal cortex, hippocampus, and accumbens.
This study reveals the temporal trends of blood-based biomarkers in psychiatric disorders and their correlations with brain structure, aiding early detection and potentially enhancing clinical outcomes.
了解血液生物标志物的时间趋势及其与脑结构的关联对于精神疾病的早期检测和干预至关重要。本研究旨在探讨诊断前后十年内的这些趋势，以及与脑结构的横断面关系。
利用英国生物银行的数据，我们对在基线后10年内被诊断为焦虑症（n = 27216）、双相情感障碍（n = 1325）、抑郁症（n = 36570）或精神分裂症（n = 1478）的40 - 69岁个体进行了巢式病例对照分析。我们使用多变量线性回归分析31种血细胞计数、28种生化标志物和168种血清代谢物的时间趋势和脑结构关联。
我们发现，与对照组相比，焦虑症、双相情感障碍、抑郁症和精神分裂症分别在39种、6种、55种和12种血液标志物中观察到显著的时间差异。确定了胱抑素C、红细胞、血红蛋白、血细胞比容和总胆红素等常见生物标志物。生物标志物聚集成具有线性或非线性趋势的组。在呈线性变化的生物标志物中，一些与对照组的差异在扩大，而另一些则在缩小。例如，在抑郁症患者中，高密度脂蛋白 - 甘油三酯随时间的差异在增加，而胆固醇则呈下降趋势。非线性聚类通常在诊断前后显示出逆转，表明可能存在治疗效果。在生物标志物与脑区（包括眶额皮质、海马体和伏隔核）之间发现了差异关联。
本研究揭示了精神疾病中血液生物标志物的时间趋势及其与脑结构的相关性，有助于早期检测并可能改善临床结果。
