HPA轴系统多基因−亲子关系交互对青少年抑郁发展影响及性别差异

doi:10.12139/j.1672-0628.2026.01.009

摘要/Abstract

摘要：

抑郁是青少年常见的心理适应问题，其演变过程受到遗传易感性与家庭关系等因素的共同影响。本研究旨在考察HPA轴相关多基因与亲子互动之间的交互作用，如何影响青少年抑郁的发展路径。本研究采用纵向追踪设计，分三次时间节点收集594名初一年级学生的问卷数据与基因信息。通过潜变量增长模型，对青少年抑郁的起始状态及其变化速率进行分析，着重探讨基因与亲子关系的交互效应以及性别差异。结果表明，青少年抑郁呈现出逐渐上升的线性趋势，亲子关系预测青少年抑郁的初始水平。此外，HPA轴多基因评分与亲子关系之间的交互作用在预测青少年抑郁起始水平时呈现显著影响，但对随时间变化的增长速率不显著。性别差异分析显示，女生更易受到亲子关系和遗传因素的影响，这不仅体现在抑郁初始水平上，也影响其发展速度，结果提示干预措施应特别关注亲子关系和遗传风险的作用。

关键词: 青少年抑郁, HPA轴基因, 亲子关系, 发展轨迹

Abstract:

The current study investigated the impact of the cumulative score of HPA-axis-related multilocus genetic profile scores (MGPS) and parent-child relationships on the developmental trajectory of adolescent depression. The sample consisted of 594 first-year students from a middle school in Hunan Province, China, collected through a longitudinal study design. Three waves of questionnaire data and genetic information were gathered. By using a latent growth curve model (LGCM), the initial levels and growth rates of adolescent depression were analyzed, with a particular focus on the interaction between genetic factors and parent-child relationships, as well as gender differences. Results indicated a linear increase in adolescent depression over time, and parent-child relationships significantly predicted the initial level of adolescent depression. Furthermore, the interaction between HPA-axis MGPS and parent-child relationships notably influenced the initial level of adolescent depression, but was not significantly associated with its growth rate over time. Gender analysis revealed that female adolescents were more susceptible to the combined influence of parent-child relationships and genetic factors, impacting both the initial levels and the developmental trajectory of adolescent depression. These findings suggest that intervention strategies should prioritize the roles of parent-child relationships and genetic vulnerability.

Key words: adolescent depression, HPA axis genes, parent-child relationships, developmental trajectory

曾子豪, 何震, 袁言云, 赵纤, 印利红, 谭嵘, 常梦梦, 胡义秋. HPA轴系统多基因−亲子关系交互对青少年抑郁发展影响及性别差异[J]. 心理与行为研究, 2026, 24(1): 78-86.

Zihao ZENG, Zhen HE, Yanyun YUAN, Xian ZHAO, Lihong YIN, Rong TAN, Mengmeng CHANG, Yiqiu HU. The Impact of HPA Axis System Polygenes and Parent-Child Interaction on Adolescent Depression Development and Gender Differences[J]. Studies of Psychology and Behavior, 2026, 24(1): 78-86.

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参考文献 0

	曹衍淼, 方惠慈, 朱欣悦, 纪林芹, 张文新. BDNF基因、同伴关系与青少年早期抑郁: 基于动态发展视角. 心理学报, 2023, 55 (10): 1620- 1636.
	傅小兰, 张侃. (2023). 中国国民心理健康发展报告(2021—2022). 北京: 社会科学文献出版社.
	谭德琴, 丁菀, 宋省成, 吴伟, 蔺秀云. 代际间的暴力传递——父母虐待对儿童欺负行为的影响: 基于潜变量增长模型的分析. 心理发展与教育, 2025, 41 (3): 410- 419. DOI
	万雨霞, 焦丹阳, 张莉, 刘春雨, 王言, 胡晓倩, 王美萍. 父母教养行为与青少年早期抑郁的关系: 多基因与负性生活事件的调节作用. 心理科学, 2023, 46 (1): 203- 211.
	辛国刚, 张李斌, 常睿生, 张云运. 青少年早期受欺凌发展轨迹: 抑郁、自尊和学业成就的预测作用. 心理发展与教育, 2023, 39 (4): 568- 579. DOI
	曾子豪, 刘双金, 杨琴, 王宏才, 刘承珍, 赵纤, 胡义秋. 童年期创伤后亲子关系对青少年社会适应的影响: HPA轴系统多基因的调节. 心理学报, 2024, 56 (8): 1091- 1109.
	Andresen, E. M., Malmgren, J. A., Carter, W. B., & Patrick, D. L. Screening for depression in well older adults: Evaluation of a short form of the CES-D. American Journal of Preventive Medicine, 1994, 10 (2): 77- 84.
	Bakermans-Kranenburg, M. J., & van Ijzendoorn, M. H. Differential susceptibility to rearing environment depending on dopamine-related genes: New evidence and a meta-analysis. Development and Psychopathology, 2011, 23 (1): 39- 52.
	Banerjee, D., & Rai, M. Social isolation in COVID-19: The impact of loneliness. International Journal of Social Psychiatry, 2020, 66 (6): 525- 527.
	Bourne, S. V., Korom, M., & Dozier, M. Consequences of inadequate caregiving for children’s attachment, neurobiological development, and adaptive functioning. Clinical Child and Family Psychology Review, 2022, 25 (1): 166- 181.
	Buchanan, C. M., Maccoby, E. E., & Dornbusch, S. M. Caught between parents: Adolescents’ experience in divorced homes. Child Development, 1991, 62 (5): 1008- 1029.
	Callaghan, B. L., Gee, D. G., Gabard-Durnam, L., Telzer, E. H., Humphreys, K. L., Goff, B., ... Tottenham, N. Decreased amygdala reactivity to parent cues protects against anxiety following early adversity: An examination across 3 years. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2019, 4 (7): 664- 671.
	Dunn, E. C., Uddin, M., Subramanian, S. V., Smoller, J. W., Galea, S., & Koenen, K. C. Research review: Gene-environment interaction research in youth depression—A systematic review with recommendations for future research. Journal of Child Psychology and Psychiatry, 2011, 52 (12): 1223- 1238.
	Ellis, B. J., & Boyce, W. T. Biological sensitivity to context. Current Directions in Psychological Science, 2008, 17 (3): 183- 187.
	Fancourt, D., Steptoe, A., & Bu, F. F. Trajectories of anxiety and depressive symptoms during enforced isolation due to COVID-19 in England: A longitudinal observational study. The Lancet Psychiatry, 2021, 8 (2): 141- 149.
	Gerhard, D. M., Meyer, H. C., & Lee, F. S. An adolescent sensitive period for threat responding: Impacts of stress and sex. Biological Psychiatry, 2021, 89 (7): 651- 658.
	Howe, D. (2012). Attachment theory. In M. Gray & S. Webb (Eds.), Social work theories and methods (pp. 75–87). London: Sage Publications.
	Ising, M., Maccarrone, G., Brückl, T., Scheuer, S., Hennings, J., Holsboer, F., ... Lucae, S. FKBP5 gene expression predicts antidepressant treatment outcome in depression. International Journal of Molecular Sciences, 2019, 20 (3): 485.
	Keijser, R., Åslund, C., Nilsson, K. W., & Olofsdotter, S. Gene-environment interaction: Oxytocin receptor (OXTR) polymorphisms and parenting style as potential predictors for depressive symptoms. Psychiatry Research, 2021, 303, 114057.
	Koyama, Y., Nawa, N., Ochi, M., Surkan, P. J., & Fujiwara, T. Joint roles of oxytocin- and dopamine-related genes and childhood parenting experience in maternal supportive social network. Child Psychiatry & Human Development, 2024, 55 (3): 614- 621.
	Leadbeater, B., Thompson, K., & Gruppuso, V. Co-occurring trajectories of symptoms of anxiety, depression, and oppositional defiance from adolescence to young adulthood. Journal of Clinical Child & Adolescent Psychology, 2012, 41 (6): 719- 730.
	Masten, A. S., & Cicchetti, D. Developmental cascades. Development and Psychopathology, 2010, 22 (3): 491- 495.
	McLean, S. A., Rodgers, R. F., Slater, A., Jarman, H. K., Gordon, C. S., & Paxton, S. J. Clinically significant body dissatisfaction: Prevalence and association with depressive symptoms in adolescent boys and girls. European Child & Adolescent Psychiatry, 2022, 31 (12): 1921- 1932.
	Nabunya, P., Damulira, C., Byansi, W., Muwanga, J., Bahar, O. S., Namuwonge, F., ... Ssewamala, F. M. Prevalence and correlates of depressive symptoms among high school adolescent girls in southern Uganda. BMC Public Health, 2020, 20 (1): 1792.
	Nelemans, S. A., Boks, M., Lin, B. C., Oldehinkel, T., van Lier, P., Branje, S., & Meeus, W. Polygenic risk for major depression interacts with parental criticism in predicting adolescent depressive symptom development. Journal of Youth and Adolescence, 2021, 50 (1): 159- 176.
	Normann, C., & Buttenschøn, H. N. Gene-environment interactions between HPA-axis genes and childhood maltreatment in depression: A systematic review. Acta Neuropsychiatrica, 2020, 32 (3): 111- 121.
	Orsolini, L., Latini, R., Pompili, M., Serafini, G., Volpe, U., Vellante, F., ... De Berardis, D. Understanding the complex of suicide in depression: From research to clinics. Psychiatry Investigation, 2020, 17 (3): 207- 221.
	Pluess, M. Individual differences in environmental sensitivity. Child Development Perspectives, 2015, 9 (3): 138- 143.
	Roisman, G. I., Newman, D. A., Fraley, R. C., Haltigan, J. D., Groh, A. M., & Haydon, K. C. Distinguishing differential susceptibility from diathesis-stress: Recommendations for evaluating interaction effects. Development and Psychopathology, 2012, 24 (2): 389- 409.
	Scholte, R. H., & van Aken, M. A. (2006). Peer relations in adolescence. In S. Jackson & L. Goossens (Eds.), Handbook of adolescent development (pp. 175–199). London: Psychology Press.
	Sellers, R., Harold, G. T., Smith, A. F., Neiderhiser, J. M., Reiss, D., Shaw, D., ... Leve, L. D. Disentangling nature from nurture in examining the interplay between parent-child relationships, ADHD, and early academic attainment. Psychological Medicine, 2021, 51 (4): 645- 652.
	Starr, L. R., & Huang, M. HPA-axis multilocus genetic variation moderates associations between environmental stress and depressive symptoms among adolescents. Development and Psychopathology, 2019, 31 (4): 1339- 1352.
	Starr, L. R., Stroud, C. B., Shaw, Z. A., & Vrshek-Schallhorn, S. Stress sensitization to depression following childhood adversity: Moderation by HPA axis and serotonergic multilocus profile scores. Development and Psychopathology, 2021, 33 (4): 1264- 1278.
	van der Ende, J., Verhulst, F. C., & Tiemeier, H. Multitrait-multimethod analyses of change of internalizing and externalizing problems in adolescence: Predicting internalizing and externalizing DSM disorders in adulthood. Journal of Abnormal Psychology, 2020, 129 (4): 343- 354.
	Weavers, B., Heron, J., Thapar, A. K., Stephens, A., Lennon, J., Jones, R. B., ... Rice, F. The antecedents and outcomes of persistent and remitting adolescent depressive symptom trajectories: A longitudinal, population-based English study. The Lancet Psychiatry, 2021, 8 (12): 1053- 1061.
	Xu, L. Y., Liu, L. S., Li, Y. F., Liu, L. J., & Huntsinger, C. S. Parent-child relationships and Chinese children’s social adaptations: Gender difference in parent-child dyads. Personal Relationships, 2018, 25 (4): 462- 479.
	Zinchuk, M. S., Druzhkova, T. A., Popova, S. B., Zhanina, M. Y., Guekht, A. B., & Gulyaeva, N. V. Early adverse family experiences and elevated adrenocorticotropic hormone predict non-suicidal self-injury in females with non-psychotic mental disorders and suicidal ideation. Biomedicines, 2023, 11 (12): 3181.

基因	位点	等位基因	MAF	MAF(1000g-CHBS)	基因型和分布			Hardy-Weinberg equilibrium
基因	位点	等位基因	MAF	MAF(1000g-CHBS)	11	12	22	χ²	p
SKA2	rs7208505	G>A	0.40	0.40	212(35.7%)	287(48.3%)	95(16.0%)	0.01	0.92
NR3C1	rs6198	T>C	0.0002	0.001	592(99.7%)	2(0.03%)	0(0%)	0.001	0.98
	rs41423247	G>C	0.22	0.22	366(61.6%)	196(32.0%)	32(5.4%)	0.60	0.44
NR3C2	rs17581262	A>G	0.18	0.19	400(67.3%)	175(29.5%)	19(3.2%)	0
FKBP5	rs1360780	C>T	0.30	0.29	292(49.2%)	243(40.9%)	59(9.9%)	0.84	0.36
	rs9470080	C>T	0.35	0.34	247(41.6%)	277(46.6%)	70(11.8%)	0.29	0.59

基因	位点	等位基因	MAF	MAF(1000g-CHBS)	基因型和分布			Hardy-Weinberg equilibrium
基因	位点	等位基因	MAF	MAF(1000g-CHBS)	11	12	22	χ²	p
SKA2	rs7208505	G>A	0.40	0.40	212(35.7%)	287(48.3%)	95(16.0%)	0.01	0.92
NR3C1	rs6198	T>C	0.0002	0.001	592(99.7%)	2(0.03%)	0(0%)	0.001	0.98
	rs41423247	G>C	0.22	0.22	366(61.6%)	196(32.0%)	32(5.4%)	0.60	0.44
NR3C2	rs17581262	A>G	0.18	0.19	400(67.3%)	175(29.5%)	19(3.2%)	0
FKBP5	rs1360780	C>T	0.30	0.29	292(49.2%)	243(40.9%)	59(9.9%)	0.84	0.36
	rs9470080	C>T	0.35	0.34	247(41.6%)	277(46.6%)	70(11.8%)	0.29	0.59

变量	1	2	3	4	5	6	7	8	9	10
T1 抑郁
T2 抑郁	0.51**
T3 抑郁	0.43**	0.58**
T1 父子关系	−0.43**	−0.32**	−0.30**
T2 父子关系	−0.33**	−0.46**	−0.39**	0.44**
T3 父子关系	−0.31**	−0.33**	−0.41**	0.42**	0.54**
T1 母子关系	−0.43**	−0.32**	−0.30**	0.98**	0.44**	0.42**
T2 母子关系	−0.31**	−0.39**	−0.33**	0.43**	0.70**	0.38**	0.43*
T3 母子关系	−0.30**	−0.29**	−0.36**	0.40**	0.36**	0.72**	0.40**	0.53**
MGPS	−0.02	−0.01	−0.02	0.06	0.06	0.03	0.07	0.08	0.06
M±SD	7.24±5.56	7.54±6.01	8.33±6.27	30.03±7.35	30.76±9.17	30.44±9.43	31.52±8.25	33.38±8.45	32.56±8.61	4.04±1.66

变量	1	2	3	4	5	6	7	8	9	10
T1 抑郁
T2 抑郁	0.51**
T3 抑郁	0.43**	0.58**
T1 父子关系	−0.43**	−0.32**	−0.30**
T2 父子关系	−0.33**	−0.46**	−0.39**	0.44**
T3 父子关系	−0.31**	−0.33**	−0.41**	0.42**	0.54**
T1 母子关系	−0.43**	−0.32**	−0.30**	0.98**	0.44**	0.42**
T2 母子关系	−0.31**	−0.39**	−0.33**	0.43**	0.70**	0.38**	0.43*
T3 母子关系	−0.30**	−0.29**	−0.36**	0.40**	0.36**	0.72**	0.40**	0.53**
MGPS	−0.02	−0.01	−0.02	0.06	0.06	0.03	0.07	0.08	0.06
M±SD	7.24±5.56	7.54±6.01	8.33±6.27	30.03±7.35	30.76±9.17	30.44±9.43	31.52±8.25	33.38±8.45	32.56±8.61	4.04±1.66

预测因素	截距	斜率	χ²(df)	CFI	TLI	RMSEA	SRMR
Model 1a: 抑郁无条件增长模型	7.22(0.22)***	0.37(0.09)***	9.71(3)	0.99	0.99	0.06	0.05
Model 1b: 父子关系无条件增长模型	30.28(0.29)***	0.10(0.12)	25.49(3)	0.94	0.94	0.11	0.14
Model 1c: 母子关系无条件增长模型	32.17(0.31)***	0.24(0.12)	32.33(3)	0.91	0.91	0.13	0.05
Model 2: 性别	1.36(0.43)***	−0.06(0.17)	0.83(2)	1.00	1.00	0.01	0.01
Model 3: HPA轴MGPS	−0.09(0.13)***	−0.01(0.05)	0.84(3)	1.00	1.00	0.01	0.01
Model 4a: 父子关系	−0.31(0.03)***	0.02(0.01)	3.20(4)	1.00	1.00	0.01	0.01
Model 5a: G×E父子模型	0.04(0.02)*	0.01(0.01)	3.81(5)	1.00	1.00	0.01	0.01
Model 4b: 母子关系	−0.26(0.02)***	0.02(0.01)	2.91(4)	1.00	1.00	0.01	0.01
Model 5b: G×E母子模型	0.03(0.02)*	0.01(0.02)	3.64(5)	1.00	1.00	0.01	0.01