Deciphering the Biological Mechanisms Underlying the Genome-Wide Associations between Computerized Device Use and Psychiatric Disorders

Frank R Wendt, Carolina Muniz Carvalho, Gita A Pathak, Joel Gelernter, Renato Polimanti, Frank R Wendt, Carolina Muniz Carvalho, Gita A Pathak, Joel Gelernter, Renato Polimanti

Abstract

Computerized device use (CDU) is societally ubiquitous but its effects on mental health are unknown. We performed genetic correlation, Mendelian randomization, and latent causal variable analyses to identify shared genetic mechanisms between psychiatric disorders (Psychiatric Genomics Consortium; 14,477 < N < 150,064) and CDU (UK Biobank; N = 361,194 individuals). Using linkage disequilibrium score regression, we detected strong genetic correlations between "weekly usage of mobile phone in last 3 months" (PhoneUse) vs. attention deficit hyperactivity disorder (ADHD; rg = 0.425, p = 4.59 × 10-29) and "plays computer games" (CompGaming) vs. schizophrenia (SCZ; rg = -0.271, p = 7.16 × 10-26). Focusing on these correlations, we used two sample MRs to detect the causal relationships between trait pairs by treating single nucleotide polymorphisms as non-modifiable risk factors underlying both phenotypes. Significant bidirectional associations were detected (PhoneUse→ADHD β = 0.132, p = 1.89 × 10-4 and ADHD→PhoneUse β = 0.084, p = 2.86 × 10-10; CompGaming→SCZ β = -0.02, p = 6.46 × 10-25 and CompGaming→SCZ β = -0.194, p = 0.005) and the latent causal variable analyses did not support a causal relationship independent of the genetic correlations between these traits. This suggests that molecular pathways contribute to the genetic overlap between these traits. Dopamine transport enrichment (Gene Ontology:0015872, pSCZvsCompGaming = 2.74 × 10-10) and DRD2 association (pSCZ = 7.94 × 10-8; pCompGaming = 3.98 × 10-25) were detected in SCZ and CompGaming and support their negative correlative relationship. FOXP2 was significantly associated with ADHD (p = 9.32 × 10-7) and PhoneUse (p = 9.00 × 10-11) with effect directions concordant with their positive genetic correlation. Our study demonstrates that epidemiological associations between psychiatric disorders and CDUs are due, in part, to the molecular mechanisms shared between them rather than a causal relationship. Our findings imply that biological mechanisms underlying CDU contribute to the psychiatric phenotype manifestation.

Keywords: DRD2; FOXP2; Mendelian randomization; attention deficit hyperactivity disorder; psychiatry; schizophrenia.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Linkage disequilibrium score regression genetic correlations for computerized device use and psychiatric disorder (attention deficit hyperactivity disorder (ADHD), alcohol dependence, autism spectrum disorder, bipolar disorder, anorexia nervosa, major depressive disorder, post-traumatic stress disorder, and schizophrenia) pairs. Large asterisks indicate genetic correlations surviving multiple testing correction (p = 1.25 × 10−3), while small asterisks indicate nominally significant genetic correlations. Genetic correlations significant after Bonferroni correction are provided in Table S1.
Figure 2
Figure 2
Genes significantly associated with both schizophrenia (SCZ) and UKB Field ID 2237 “plays computer games” (CompGaming) after Bonferroni correction (p < 2.64 × 10−6). The difference in per-gene effects (z-scoreCompGaming minus z-scoreSCZ) on each trait is color-coded.
Figure 3
Figure 3
Scatterplots showing gene set enrichment (a; N = 221 gene sets) and linkage disequilibrium score regression (b; N = 224 traits) results for gene sets and UK Biobank traits with nominally significant differences between schizophrenia and CompGaming (UKB Field ID 2237 “plays computer games”). Gene sets are labeled with gene ontology (GO), reactome (R), systematic identifiers (M), or specific study identifiers (last name of first author); the top five most significant differences in genetic correlation are labeled. Detailed results for gene set enrichment and genetic correlations surviving multiple testing correction are provided in Tables S7–S10.
Figure 4
Figure 4
Scatterplots of genetic correlation results for attention deficit hyperactivity disorder (ADHD) and PhoneUse, for both sexes combined (a; N = 841 traits), females only (b; N = 478 traits), and males only (c; N = 435 traits). Labeled traits are among the top ten most significant genetic correlations in ADHD and PhoneUse (UKB Field ID 1120 “weekly usage of mobile phone in last three months”). Detailed genetic correlation results surviving multiple testing correction are provided in Tables S21–S23.

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