2216 - APPLYING EXTENDED NETWORK ANALYSES TO IDENTIFY CENTRAL SYMPTOMS AND RISK FACTORS TRIGGERING DEPRESSION: EFFECTS OF GENDER AND CLINICAL STATUS

Session: D02S007 - Measurement Theory and Modeling 2
AUTHORS:
Semkovska Maria (University of Southern Denmark ~ Odense ~ Denmark) , Zhang Daiyan (University of Southern Denmark ~ Odense ~ Denmark)
Abstract text:
Introduction
Network theory conceptualises psychological symptoms and related risk and protective factors (e.g., cognition, daily activities) as a system of mutually interacting components. Network models allow the evaluation of each factor's unique contribution to depressive symptom severity while accounting for their mutual interactions. Applied to twin designs, they can help ascertain whether the observed associations reflect an underlying genetic vulnerability or environmental influences.


Purpose
The study examined whether the network organization of depressive symptoms, cognitive functions, and daily activities differs by gender or depression diagnosis. Gender-specific patterns of associations were assessed in a cohort of like-sex twins. Then, monozygotic twins discordant for depression were compared to evaluate environmental contributions beyond shared genetics.


Method
For the extended networks construction, measures of depressive symptoms, cognition, and daily activities (intellectual, physical, social) were obtained from 3,752 Danish like-sex twins, 1,020 women pairs (459 monozygotic) and 856 men pairs (365 monozygotic). Networks were estimated with Gaussian Graphical Models regularised with glasso, and compared with the Network Comparison Test. Monozygotic and dizygotic co-twin networks within- and between- each gender group were compared. Differences between co-twins in 147 monozygotic pairs discordant for lifetime depression were also evaluated.


Results
No significant differences were detected between monozygotic and dizygotic networks within gender. However, networks differed significantly by gender in overall strength, structure, and partial correlations linking specific depressive symptoms with risk factors. Among discordant monozygotic pairs, affected twins showed denser networks connecting depressive symptoms, cognition, and activities compared to unaffected co-twins, although the relative structure of associations was similar.


Conclusions
Gender differences in network strength appear best explained by environmental factors, with women showing stronger symptom-risk factor connectedness. In discordant monozygotic pairs, depression was associated with heightened network density, also suggesting that external events affecting the ability to feel happiness likely trigger the psychopathological process (depression network activation), independently of genetics.