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山东大学学报 (医学版) ›› 2026, Vol. 64 ›› Issue (3): 83-92.doi: 10.6040/j.issn.1671-7554.0.2025.0193

• “儿童青少年心理健康”重点专题 • 上一篇    

孟德尔随机化分析免疫细胞表型与孤独症谱系障碍的因果关联

吴志晓1,赵红洋2   

  • 发布日期:2026-03-19
  • 通讯作者: 赵红洋. E-mail:drzhaohongyang@163.com
  • 基金资助:
    “泉城学者”建设工程(P-20230825-0025)

Mendelian randomization analysis of causal associations between immune cell phenotypes and the risk of autism spectrum disorders

WU Zhixiao1, ZHAO Hongyang2   

  1. 1. Department of Medical Integration and Practice Center, Shandong University, Jinan 250012, Shandong, China;
    2. Department of Pediatrics, Jinan Central Hospital, Jinan 250013, Shandong, China
  • Published:2026-03-19

摘要: 目的 探讨免疫细胞表型与孤独症谱系障碍(autism spectrum disorder, ASD)之间的因果关系。 方法 采用双向双样本孟德尔随机化(mendelian randomization, MR)分析,利用欧洲人群全基因组关联研究(genome-wide association studies, GWAS)的公开遗传数据,以单核苷酸多态性(single nucleotide polymorphisms, SNPs)作为工具变量,主要采用逆方差加权法(inverse variance weighted, IVW)进行因果效应分析,并辅以MR-Egger回归、加权中位数、加权模式和简单模式等方法进行验证。为控制多重比较带来的假阳性结果,采用Benjamini-Hochberg方法进行错误发现率(false discovery rate, FDR)校正。通过Cochran Q检验评估工具变量的异质性,运用MR-Egger截距分析和MR-PRESSO全局测试评估水平多效性,并采用留一法进行敏感性分析。 结果 研究共纳入13 092个SNPs作为工具变量。经FDR校正后,未发现免疫细胞表型与ASD存在统计学显著关联(PFDR>0.05)。然而,在未经校正的分析中,6种低P值表型仍值得讨论,具体包括:CD8+T细胞在白细胞中百分比(OR=1.099,95%CI:1.039~1.163,PIVW=0.001)、CD20在IgD+CD38-B细胞中的表达水平(OR=1.064,95%CI:1.019~1.110,PIVW=0.005)和CD45在未成熟MDSCs中的表达水平(OR=1.056,95%CI:1.021~1.093,PIVW=0.001)与ASD风险呈正相关;而CD45在HLA DR+T细胞中的表达水平(OR=0.945,95%CI:0.906~0.986,PIVW=0.009)、CD14在CD33+HLA DR+CD14dim中的表达水平(OR=0.955,95%CI:0.925~0.987,PIVW=0.006)和CD25在CD4调节性T细胞中的表达水平(OR=0.963,95%CI:0.939~0.989,PIVW=0.005)可能对ASD具有保护作用。所有分析均未发现显著的水平多效性或异质性,敏感性分析表明结果稳健。反向MR分析未发现ASD对以上免疫细胞表型的显著影响。 结论 本研究提示特定免疫细胞表型可能与ASD发病风险存在潜在因果关系,为未来探索ASD的免疫相关生物标志物和潜在治疗靶点提供了研究方向。

关键词: 孤独症谱系障碍, 免疫细胞, 免疫细胞表型, 孟德尔随机化

Abstract: Objective To explore the causal relationship between immune cell phenotypes and autism spectrum disorder. Methods The present study utilised a bidirectional two-sample mendelian randomization analysis. The present study utilised publicly available genetic data from genome-wide association studies(GWAS)in European populations. Single-nucleotide polymorphisms(SNPs)were utilised as instrumental variables(IVs). The causal effect analysis was primarily executed using the inverse variance weighted(IVW)method, with additional validation conducted via MR-Egger regression, weighted median, weighted mode, and simple mode. In order to control for the possibility of false positive results resulting from multiple comparisons, false discovery rate(FDR)correction was performed using the Benjamini-Hochberg method. The heterogeneity of the IVs was assessed by the Cochran Q-test, while the horizontal multiple validity was tested using the MR-Egger intercept analysis and the MR-PRESSO global test. Finally, sensitivity analyses were performed using the leave-one-out method. Results A total of 13,092 SNPs were included in the study as IVs. Following FDR correction(PFDR>0.05), no statistically significant association was identified between immune cell phenotypes and ASD. Nevertheless, six low P-value phenotypes merit further discussion in the uncorrected analysis. Specifically, the percentage of CD8+T cells in leukocytes(OR=1.099,95%CI:1.039-1.163, PIVW=0.001), the expression level of CD20 in lgD+CD38-B cells(OR=1.064, 95%CI:1.019-1.110, PIVW=0.005)and the expression level of CD45 in immature MDSCs(OR=1.056,95%CI: 1.021-1.093, PIVW=0.001)may incease ASD risk. In addition, CD45 expression level in HLA DR+ T cells(OR=0.945, 95%CI:0.906-0.986, PIVW=0.009), CD14 expression level in CD33+HLA DR+CD14 dim(OR=0.955, 95%CI:0.925-0.987, PIVW=0.006)and CD25 expression level in CD4 regulatory T cells(OR=0.963, 95% CI:0.939-0.989, PIVW=0.005)may have a protective effect against ASD. The analyses did not reveal any substantial horizontal pleiotropy or heterogeneity. Sensitivity analyses indicated robust results. Conversely, reverse MR analysis did not demonstrate a substantial impact of ASD on the aforementioned immunophenotype. Conclusion The present study suggests that specific immune cell phenotypes may have a potential causal relationship with the risk of ASD development, and provides a research direction for future exploration of immune-related biomarkers and potential therapeutic targets for ASD.

Key words: Autism spectrum disorder, Immune cell, Immune cell phenotype, Mendelian randomization

中图分类号: 

  • R749.94
[1] Maenner MJ, Shaw KA, Bakian AV, et al. Prevalence and characteristics of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2018[J]. MMWR Surveill Summ, 2021, 70(11): 1-16.
[2] Maenner MJ, Warren Z, Williams AR, et al. Prevalence and characteristics of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2020[J]. MMWR Surveill Summ, 2023, 72(2): 1-14.
[3] Zhou H, Xu X, Yan WL, et al. Prevalence of autism spectrum disorder in China: a nationwide multi-center population-based study among children aged 6 to 12 years[J]. Neurosci Bull, 2020, 36(9): 961-971.
[4] Battle DE. Diagnostic and statistical manual of mental disorders(DSM)[J]. Codas, 2013, 25(2): 191-192.
[5] Lord C, Elsabbagh M, Baird G, et al. Autism spectrum disorder[J]. Lancet, 2018, 392(10146): 508-520.
[6] Xiong Y, Chen JH, Li YB. Microglia and astrocytes underlie neuroinflammation and synaptic susceptibility in autism spectrum disorder[J]. Front Neurosci, 2023, 17: 1125428. doi: 10.3389/fnins.2023.1125428
[7] 王斌, 付佳佳, 张翠芳, 等. 孕期环境危险因素与孤独症谱系障碍病因学关系的研究进展[J]. 中国健康心理学杂志, 2022, 30(10): 1594-1600. WANG Bin, FU Jiajia, ZHANG Cuifang, et al. Advances in the relationship between prenatal environmental risk factors and autism spectrum disorder[J]. China Journal of Health Psychology, 2022, 30(10): 1594-1600.
[8] Ellul P, Rosenzwajg M, Peyre H, et al. Regulatory T lymphocytes/Th17 lymphocytes imbalance in autism spectrum disorders: evidence from a meta-analysis[J]. Mol Autism, 2021, 12(1): 68. doi: 10.1186/s13229-021-00472-4
[9] De Giacomo A, Gargano CD, Simone M, et al. B and T immunoregulation: a new insight of B regulatory lymphocytes in autism spectrum disorder[J]. Front Neurosci, 2021, 15: 732611. doi: 10.3389/fnins.2021.732611
[10] Wu Q, Liu SL, Huang XR, et al. Bidirectional Mendelian randomization study of psychiatric disorders and Parkinsons disease[J]. Front Aging Neurosci, 2023, 15: 1120615. doi: 10.3389/fnagi.2023.1120615
[11] Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies[J]. Hum Mol Genet, 2014, 23(R1): R89-R98.
[12] Orrù V, Steri M, Sidore C, et al. Complex genetic signatures in immune cells underlie autoimmunity and inform therapy[J]. Nat Genet, 2020, 52(10): 1036-1045.
[13] Fei YC, Yu H, Wu YL, et al. The causal relationship between immune cells and ankylosing spondylitis: a bidirectional Mendelian randomization study[J]. Arthritis Res Ther, 2024, 26(1): 24. doi: 10.1186/s13075-024-03266-0
[14] Chen JB, Yu XZ, Wu XY, et al. Causal relationships between gut microbiota, immune cell, and non-small cell lung cancer: a two-step, two-sample Mendelian randomization study[J]. J Cancer, 2024, 15(7): 1890-1897.
[15] Yuan JQ, Xiong XQ, Zhang B, et al. Genetically predicted C-reactive protein mediates the association between rheumatoid arthritis and atlantoaxial subluxation[J]. Front Endocrinol(Lausanne), 2022, 13: 1054206. doi: 10.3389/fendo.2022.1054206
[16] Levin MG, Judy R, Gill D, et al. Genetics of height and risk of atrial fibrillation: a Mendelian randomization study[J]. PLoS Med, 2020, 17(10): e1003288. doi: 10.1371/journal.pmed.1003288
[17] Bowden J, Davey Smith G, Haycock PC, et al. Consis-tent estimation in mendelian randomization with some invalid instruments using a weighted median estimator[J]. Genet Epidemiol, 2016, 40(4): 304-314.
[18] Glickman ME, Rao SR, Schultz MR. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies[J]. J Clin Epidemiol, 2014, 67(8): 850-857.
[19] Verbanck M, Chen CY, Neale B, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases[J]. Nat Genet, 2018, 50(5): 693-698.
[20] Cohen JF, Chalumeau M, Cohen R, et al. Cochrans Q test was useful to assess heterogeneity in likelihood ratios in studies of diagnostic accuracy[J]. J Clin Epidemiol, 2015, 68(3): 299-306.
[21] Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method[J]. Eur J Epidemiol, 2017, 32(5): 377-389.
[22] Kumar BV, Connors TJ, Farber DL. Human T cell development, localization, and function throughout life[J]. Immunity, 2018, 48(2): 202-213.
[23] Diao HT, Pipkin M. Stability and flexibility in chromatin structure and transcription underlies memory CD8 T-cell differentiation[J]. F1000Res, 2019, 8: F1000 Faculty Rev-F1000 Faculty1278. doi: 10.12688/f1000research.18211.1
[24] Herndler-Brandstetter D, Ishigame H, Shinnakasu R, et al. KLRG1+ effector CD8+ T cells lose KLRG1, differentiate into all memory T cell lineages, and convey enhanced protective immunity[J]. Immunity, 2018, 48(4): 716-729.
[25] López-Cacho JM, Gallardo S, Posada M, et al. Characterization of immune cell phenotypes in adults with autism spectrum disorders[J]. J Investig Med, 2016, 64(7): 1179-1185.
[26] Uddin MN, Yao YY, Manley K, et al. Development, phenotypes of immune cells in BTBR T+Itpr3tf/J mice[J]. Cell Immunol, 2020, 358: 104223. doi: 10.1016/j.cellimm.2020.104223
[27] DiStasio MM, Nagakura I, Nadler MJ, et al. T lymphocytes and cytotoxic astrocyte blebs correlate across autism brains[J]. Ann Neurol, 2019, 86(6): 885-898.
[28] 马如意, 范广祥, 陈依文, 等. 小胶质细胞调节孤独症谱系障碍的作用机制研究进展[J]. 生命科学, 2024, 36(4): 477-486. MA Ruyi, FAN Guangxiang, CHEN Yiwen, et al. Advances in regulatory roles and mechanisms of microglia in autism spectrum disorders[J]. Chinese Bulletin of Life Sciences, 2024, 36(4): 477-486.
[29] Shi ZS, Yu P, Lin WJ, et al. Microglia drive transient insult-induced brain injury by chemotactic recruitment of CD8+ T lymphocytes[J]. Neuron, 2023, 111(5): 696-710.
[30] Gregg JP, Lit L, Baron CA, et al. Gene expression changes in children with autism[J]. Genomics, 2008, 91(1): 22-29.
[31] Shin B, Hosokawa H, Romero-Wolf M, et al. Runx1 and Runx3 drive progenitor to T-lineage transcriptome conversion in mouse T cell commitment via dynamic genomic site switching[J]. Proc Natl Acad Sci USA, 2021, 118(4): e2019655118. doi: 10.1073/pnas.2019655118
[32] Terrabuio E, Zenaro E, Constantin G. The role of the CD8+ T cell compartment in ageing and neurodegenerative disorders[J]. Front Immunol, 2023, 14: 1233870. doi: 10.3389/fimmu.2023.1233870
[33] Pavlasova G, Mraz M. The regulation and function of CD20: an “Enigma” of B-cell biology and targeted the-rapy[J]. Haematologica, 2020, 105(6): 1494-1506.
[34] Connolly AM, Chez M, Streif EM, et al. Brain-derived neurotrophic factor and autoantibodies to neural antigens in sera of children with autistic spectrum disorders, Landau-Kleffner syndrome, and epilepsy[J]. Biol Psychiatry, 2006, 59(4): 354-363.
[35] Piras IS, Haapanen L, Napolioni V, et al. Anti-brain antibodies are associated with more severe cognitive and behavioral profiles in Italian children with Autism Spectrum Disorder[J]. Brain Behav Immun, 2014, 38: 91-99.
[36] Heuer LS, Rose M, Ashwood P, et al. Decreased levels of total immunoglobulin in children with autism are not a result of B cell dysfunction[J]. J Neuroimmunol, 2012, 251(1/2): 94-102.
[37] Arteaga-Henríquez G, Lugo-Marín J, Gisbert L, et al. Activation of the monocyte/macrophage system and abnormal blood levels of lymphocyte subpopulations in individuals with autism spectrum disorder: a systematic review and meta-analysis[J]. Int J Mol Sci, 2022, 23(22): 14329. doi: 10.3390/ijms232214329
[38] Nadeem A, Ahmad SF, Al-Harbi NO, et al. Imbalance in pro-inflammatory and anti-inflammatory cytokines milieu in B cells of children with autism[J]. Mol Immunol, 2022, 141: 297-304.
[39] Gabrilovich DI, Bronte V, Chen SH, et al. The terminology issue for myeloid-derived suppressor cells[J]. Cancer Res, 2007, 67(1): 425;authorreply426. doi: 10.1158/0008-5472.CAN-06-3037
[40] Wu YZ, Yi M, Niu MK, et al. Myeloid-derived suppressor cells: an emerging target for anticancer immunotherapy[J]. Mol Cancer, 2022, 21(1): 184. doi: 10.1186/s12943-022-01657-y
[41] Kumar V, Cheng PY, Condamine T, et al. CD45 phosphatase inhibits STAT3 transcription factor activity in myeloid cells and promotes tumor-associated macrophage differentiation[J]. Immunity, 2016, 44(2): 303-315.
[42] Ahmad SF, Ansari MA, Nadeem A, et al. Involvement of CD45 cells in the development of autism spectrum disorder through dysregulation of granulocyte-macrophage colony-stimulating factor, key inflammatory cytokines, and transcription factors[J]. Int Immunopharmacol, 2020, 83: 106466. doi: 10.1016/j.intimp.2020.106466
[43] Alhosaini K, Ansari MA, Nadeem A, et al. Dysregulation of ki-67 expression in T cells of children with autism spectrum disorder[J]. Children(Basel), 2021, 8(2): 116. doi: 10.3390/children8020116
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