The Impact of HPA Axis System Polygenes and Parent-Child Interaction on Adolescent Depression Development and Gender Differences

doi:10.12139/j.1672-0628.2026.01.009

Abstract

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

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

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.

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.

Figures/Tables 5

References 0

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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