Psychological medicine · 2026
Education shares distinct genetic influences with substance use and disorder.
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Davis Christal N, Khan Yousef, Piserchia Zachary, Gray Joshua C, Kranzler Henry R
Аннотация
BACKGROUND: Educational attainment (EA), which comprises cognitive (CogEA) and noncognitive (NonCogEA) components, is positively genetically correlated with alcohol and cannabis use but negatively correlated with alcohol and cannabis use disorders (AUD and CUD). These paradoxical associations suggest that shared genetic influences with EA may differ by level of substance involvement.
METHODS: To test this, we examined the shared genetic architecture of EA, CogEA, and NonCogEA with alcohol consumption (AC), AUD, lifetime cannabis use (CanUse), and CUD. We used bivariate causal mixture models, local genetic correlation analyses, and conditional/conjunctional false discovery rate analyses to identify global, regional, and variant-level overlap for EA and substance-related trait pairs.
RESULTS: EA shared 57.57% of causal variants with AC and 62.42% with AUD, while sharing 48.07% of causal variants with CanUse and 84.18% with CUD. Among shared variants for AC, 48.12% had concordant effects with CogEA and 52.86% with NonCogEA. For AUD, 38.40% and 41.02% of causal variants had concordant effects with CogEA and NonCogEA, respectively. CanUse had higher concordance with CogEA (71.42%) and NonCogEA (65.56%) than CUD (37.97% and 42.23%, respectively). Functional enrichment in brain tissues varied across substance use and EA pairs.
CONCLUSIONS: EA is associated with greater alcohol and cannabis use and lower risk for AUD and CUD, a pattern that reflects both concordant and discordant variant effects. CogEA and NonCogEA show partially distinct patterns, particularly for cannabis-related traits, highlighting the importance of disaggregating EA to clarify the genetic architecture underlying its paradoxical associations with substance-related traits.
METHODS: To test this, we examined the shared genetic architecture of EA, CogEA, and NonCogEA with alcohol consumption (AC), AUD, lifetime cannabis use (CanUse), and CUD. We used bivariate causal mixture models, local genetic correlation analyses, and conditional/conjunctional false discovery rate analyses to identify global, regional, and variant-level overlap for EA and substance-related trait pairs.
RESULTS: EA shared 57.57% of causal variants with AC and 62.42% with AUD, while sharing 48.07% of causal variants with CanUse and 84.18% with CUD. Among shared variants for AC, 48.12% had concordant effects with CogEA and 52.86% with NonCogEA. For AUD, 38.40% and 41.02% of causal variants had concordant effects with CogEA and NonCogEA, respectively. CanUse had higher concordance with CogEA (71.42%) and NonCogEA (65.56%) than CUD (37.97% and 42.23%, respectively). Functional enrichment in brain tissues varied across substance use and EA pairs.
CONCLUSIONS: EA is associated with greater alcohol and cannabis use and lower risk for AUD and CUD, a pattern that reflects both concordant and discordant variant effects. CogEA and NonCogEA show partially distinct patterns, particularly for cannabis-related traits, highlighting the importance of disaggregating EA to clarify the genetic architecture underlying its paradoxical associations with substance-related traits.