Alcohol reverses the effects ofKCNJ6(GIRK2) noncoding variants on excitability of human glutamatergic neurons

Abstract

Synonymous and noncoding single nucleotide polymorphisms (SNPs) in the KCNJ6 gene, encoding G protein-gated inwardly rectifying potassium (GIRK2) channel subunit 2, have been linked with increased electroencephalographic frontal theta event-related oscillations (ERO) in subjects diagnosed with alcohol use disorder (AUD). To identify molecular and cellular mechanisms while retaining the appropriate genetic background, we generated induced excitatory glutamatergic neurons (iN) from iPSCs derived from four AUD-diagnosed subjects with KCNJ6 variants (Affected: AF) and four control subjects without variants (Unaffected: UN). Neurons were analyzed for changes in gene expression, morphology, excitability and physiological properties. Single cell RNA sequencing suggests that KCNJ6 AF variant neurons have altered patterns of synaptic transmission and cell projection morphogenesis. Results confirm that AF neurons express lower levels of GIRK2, have greater neurite area, and elevated excitability. Interestingly, exposure to intoxicating concentrations of ethanol induces GIRK2 expression and reverses functional effects in AF neurons. Ectopic overexpression of GIRK2 alone mimics the effect of ethanol to normalize induced excitability. We conclude that KCNJ6 variants decrease GIRK2 expression and increase excitability and that this effect can be minimized or reduced with ethanol.

The collaborative study on the genetics of alcoholism: Genetics

“…The role of KCNJ6 in alcohol‐ and other reward‐related behaviors is supported by multiple independent studies. 100 , 101 , 102 , 103 , 104 , 105 Pursuing this gene using iPSC derived neurons and lymphocytes from COGA participants with and without AUD, we recently showed that neurons derived from AUD COGA subjects express lower levels of GIRK2 and that exposure to levels of ethanol consistent with the human phenotype of intoxication reverses these functional effects 100 (see, 5. Functional Genomics).…”