Commonly-occurring polymorphisms in the COMT, DRD1 and DRD2 genes influence different aspects of motor sequence learning in humans

Abstract

Performing sequences of movements is a ubiquitous skill that involves dopamine transmission. However, it is unclear which components of the dopamine system contribute to which aspects of motor sequence learning. Here we used a genetic approach to investigate the relationship between different components of the dopamine system and specific aspects of sequence learning in humans. In particular, we investigated variations in genes that code for the catechol-O-methyltransferase (COMT) enzyme, the dopamine transporter (DAT) and dopamine D1 and D2 receptors (DRD1 and DRD2). COMT and the DAT regulate dopamine availability in the prefrontal cortex and the striatum, respectively, two key regions recruited during learning, whereas dopamine D1 and D2 receptors are thought to be involved in long-term potentiation and depression, respectively. We show that polymorphisms in the COMT, DRD1 and DRD2 genes differentially affect behavioral performance on a sequence learning task in 161 Caucasian participants. The DRD1 polymorphism predicted the ability to learn new sequences, the DRD2 polymorphism predicted the ability to perform a previously learnt sequence after performing interfering random movements, whereas the COMT polymorphism predicted the ability to switch flexibly between two sequences. We used computer simulations to explore potential mechanisms underlying these effects, which revealed that the DRD1 and DRD2 effects are possibly related to neuroplasticity. Our prediction-error algorithm estimated faster rates of connection strengthening in genotype groups with presumably higher D1 receptor densities, and faster rates of connection weakening in genotype groups with presumably higher D2 receptor densities. Consistent with current dopamine theories, these simulations suggest that D1-mediated neuroplasticity contributes to learning to select appropriate actions, whereas D2-mediated neuroplasticity is involved in learning to inhibit incorrect action plans. However, the learning algorithm did not account for the COMT effect, suggesting that prefrontal dopamine availability might affect sequence switching via other, non-learning, mechanisms. These findings provide insight into the function of the dopamine system, which is relevant to the development of treatments for disorders such as Parkinson's disease. Our results suggest that treatments targeting dopamine D1 receptors may improve learning of novel sequences, whereas those targeting dopamine D2 receptors may improve the ability to initiate previously learned sequences of movements.

Pharmacological Mechanisms Underlying the Neuroprotective Effects of Alpinia oxyphylla Miq. on Alzheimer’s Disease

“…Neurotransmitters, such as dopamine (DA, hsa04728), serotonin (5-HT, hsa04726), and acetylcholine (ACh, has04725) work on muscarinic acetylcholine receptor M2 (CHRM2) [46] and MAOA for DA metabolism in glial cells, as well as on CHRNA7 [47] and CHRM1 [48] for calcium (Ca 2+ ) storage by Ca 2+ -induced Ca 2+ release (CICR) [49], and on HTR2A-SLC6A4-IP3-TRPC1 [50,51] pathway for Ca 2+ transport, respectively. On the postsynaptic cell membrane, DA, is the prototypical slow neurotransmitter of the mammalian brain, which interacts with D1-like receptors DRD1 and DRD5 [52,53], both positively coupled to adenylyl cyclase (AC) and cAMP production, which are activated and regulated downstream of PTGS1 and NOS1 expression. While the activation of D2-like receptors DRD2, DRD3, and DRD4 have exactly the reverse effect on regulating the production of AC and cAMP in dopaminergic synapse pathway The left panel of Figure 6 shows that SLC18A1, 2, and 3 may have a role in synaptic vesicle cycling, acetylcholinesterase (ACHE) [42], and amine oxidase [flavin-containing] A (MAOA) [43,44] signaling, which have been shown to be involved in tryptophan metabolism, clycerophospholipid metabolism, and also related to cocaine and amphetamine addiction, as well as alcoholism, and Parkinson's disease in the presynaptic nerve terminal.…”

Age‐related differences in sequence learning: Findings from two visuo‐motor sequence learning tasks

“…The sequence learning tasks were similar to the ones we previously used (see Baetu, Burns, Urry, Barbante, & Pitcher, ; Urry et al ., ). The SRTT and PSLT were matched in appearance and sequences.…”

Polymorphisms that affect GABA neurotransmission predict processing of aversive prediction errors in humans

“…Most computational models of learning rely on prediction error to alter connections (e.g., Baetu et al, 2015;Rescorla & Wagner, 1972;McLaren & Mackintosh, 2002;Sutton & Barto, 1987). Prediction error is a formalisation of the concept of surprise and reflects the extent to which the US was not anticipated.…”