Cumulative Dopamine Genetic Score predicts behavioral and electrophysiological correlates of response inhibition via interactions with task demand

Abstract

Functional genetic polymorphisms in the brain dopamine (DA) system have been suggested to underlie individual differences in response inhibition, namely the suppression of a prepotent or inappropriate action. However, findings on associations between single DA polymorphisms and inhibitory control often are mixed, partly due to their small effect sizes. In the present study, a cumulative genetic score (CGS) was used: alleles previously associated with both impulsive behavior and lower baseline DA level, precisely the DRD4 Exon III 7-repeat, DAT1 VNTR 10-repeat and the COMT 158val allele, each added a point to the DA-CGS. Participants (N = 128) completed a Go/No-Go task varying in difficulty and EEG recordings were made with focus on the NoGo-P3, an ERP that reflects inhibitory response processes. We found a higher DA-CGS (lower basal/tonic DA level) to be associated with better performance (lower %FA and more adaptive responding) in the very demanding/rapid than in the less demanding/rapid condition, whereas the reverse pattern was true for individuals with a lower DA-CGS. A similar interaction pattern of DA-CGS and task condition was found for NoGo-P3 amplitude. In line with assumptions of distinct optimum DA levels for different cognitive demands, a DA-CGS-dependent variation of tonic DA levels could have modulated the balance between cognitive stability and flexibility, thereby affecting the optimal DA level required for the specific task condition. Moreover, a task demand-dependent phasic DA release might have added to the DA-CGS-related basal/tonic DA levels, thereby additionally affecting the balance between flexibility and stability, in turn influencing performance and NoGo-P3.

Dopamine Receptor Subtypes, Physiology and Pharmacology: New Ligands and Concepts in Schizophrenia

“…(Tseng et al, 2017;Purves-Tyson et al, 2017) Genetic/ epigenetic DA sensitization in SCZ./NMDA DR epigenetic./Cumulative DA genetic and response inhibition./DR genetic variants and heterodimerization. (Oishi et al, 2020;Enge et al, 2020;Faron-Gorecka et al, 2020;Jackson, 2020) Transcriptional SCZ risk genes control on D2 pathway expression. (Torretta et al, 2020)…”

Cumulative Genetic Score of DRD2 Polymorphisms Is Associated with Impulsivity and Masked Semantic Priming

“…In accordance with previous studies using CGS analysis (e.g. Enge et al 2020 ), participants’ DRD2-CGS was calculated by adding the numbers of alleles previously associated with lower dopaminergic neurotransmission, as outlined above, assuming a linear model. In short, the number of T alleles of the rs1800497 (TT: 6, TC: 46, CC: 103; HWE: χ 2 (1) = 0.09, p = .762), the number of T alleles of the rs2283265 (TT: 4, TG: 40, GG: 111; HWE: χ 2 (1) = 0.03, p = .862), the number of C alleles of the rs6277 (TT: 45, TC: 78, CC: 32; HWE: χ 2 (1) = 0.03, p = .866), the number of T alleles of the rs12364283 (TT: 126, TC: 27, CC: 2; HWE: χ 2 (1) = 0.16, p = .688), the number of C alleles of the rs2242592 (TT: 76, TC: 66, CC: 13; HWE: χ 2 (1) = 0.06, p = .802) and the number of T alleles of the rs4648317 (TT: 3, TC: 37, CC: 115; HWE: χ 2 (1) = 0.00, p = .992) were added, resulting in a CGS ranging from 0 to 12 (Table 1 ).…”

“…The aggregation of the usually small effects of single polymorphisms with similar functionality may increase the variance explained while avoiding type I error inflation due to multiple testing (e.g. Enge et al 2020 ). Therefore, in this study, we investigate six DRD2 polymorphisms that have been shown to be functionally relevant in previous studies: rs1800497, rs2283265, rs6277, rs12364283, rs2242592 and rs4648317.…”

Do shorter inter‐stimulus intervals in the go/no‐go task enable better assessment of response inhibition?

“…This variability seems to be related to the difficulty of the task because, in previous studies that used the GNG with several characteristics yet retained a sample with the same attribute, the number of commission errors varied among studies. For example, among previous studies of university students, Enge, Sach, Reif, Lesch, Miller and Fleischhauer (2020) reported about 30% of commission error rate in the GNG, while Caswell, Bond, Duka and Morgan (2015) and Hasegawa, Somatori, Nishimura, Hattori and Kunisato (2019) showed about 3% of commission error rate. Hasegawa et al .…”