Polygenic Scores and Networks of Psychopathology Symptoms

Abstract

Importance: Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology.

Objective: To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms.

Design, setting, and participants: Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included.

Main outcomes and measures: Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS.

Results: Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = -0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041).

Conclusions and relevance: Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity.

Figure 1.. Analysis Flow of the Study, Including Network Analysis in the Avon Longitudinal Study of Parents and Children (ALSPAC) and Replication in the Twin Early Development Study (TEDS)

ADHD indicates attention-deficit/hyperactivity disorder; ANX, anxiety; BMI, body mass index; DEP, depression; EA, educational attainment; GLASSO, graphical least absolute shrinkage and selection operator; PC, principal component; PGS, polygenic score; SDQ, Strength and Difficulties Questionnaire; SMFQ, Short Mood and Feelings Questionnaire.

Figure 2.. Networks of Psychiatric Polygenic Scores (PGSs) and Psychopathology Symptoms

Plots of networks with depression PGS, anxiety PGS, attention-deficit/hyperactivity disorder (ADHD) PGS. Partial correlations between scale items are drawn in the plot when |r| > 0.1 for clarity (ie, the threshold for qgraph visualization of edges connecting scale items is 0.1). All partial correlations between PGS nodes and scale items are drawn (ie, qgraph visualization threshold is 0 for edges connecting PGS). Blue edges connecting PGSs indicate positive associations. All edges connecting scale items are solid gray when positive and dotted gray when negative. Bold items in the legend indicate nodes connected to a PGS. PGSs are in the center of each graph, and all other nodes are positioned according to an average layout obtained with the Fruchterman-Reingold algorithm. eFigure 1 in Supplement 1 includes all networks without thresholds and common layout. ANX indicates anxiety; COND, conduct problems; DEP, depression; EMO, emotional problems; HYP, hyperactivity problems; PEER, peer problems; PRO, prosocial scale.

Figure 3.. Networks of Nonpsychiatric Polygenic Scores (PGSs) and Psychopathology Symptoms

Plots of networks with body mass index (BMI) PGS and educational attainment (EA) PGS. Partial correlations between scale items are drawn in the plot when |r| > 0.1 for clarity, and all partial correlations between PGS nodes and scale items are drawn. All edges connecting PGS are blue when positive and red when negative. All edges connecting scale items are solid gray when positive and dotted gray when negative. Bold items in the legend indicate nodes connected to a PGS. PGSs are in the center of each graph and all other nodes are positioned according to an average layout obtained with the Fruchterman-Reingold algorithm. COND indicates conduct problems; DEP, depression; EMO, emotional problems; HYP, hyperactivity problems; PEER, peer problems; PRO, prosocial scale.