Dataset Information

Fronto-striatal gray matter contributions to discrimination learning in Parkinson's disease.

ABSTRACT: Discrimination learning deficits in Parkinson's disease (PD) have been well-established. Using both behavioral patient studies and computational approaches, these deficits have typically been attributed to dopamine imbalance across the basal ganglia. However, this explanation of impaired learning in PD does not account for the possible contribution of other pathological changes that occur in the disease process, importantly including gray matter loss. To address this gap in the literature, the current study explored the relationship between fronto-striatal gray matter atrophy and learning in PD. We employed a discrimination learning task and computational modeling in order to assess learning rates in non-demented PD patients. Behaviorally, we confirmed that learning rates were reduced in patients relative to controls. Furthermore, voxel-based morphometry imaging analysis demonstrated that this learning impairment was directly related to gray matter loss in discrete fronto-striatal regions (specifically, the ventromedial prefrontal cortex, inferior frontal gyrus and nucleus accumbens). These findings suggest that dopaminergic imbalance may not be the sole determinant of discrimination learning deficits in PD, and highlight the importance of factoring in the broader pathological changes when constructing models of learning in PD.

SUBMITTER: O'Callaghan C

PROVIDER: S-EPMC3859902 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Fronto-striatal gray matter contributions to discrimination learning in Parkinson's disease.

O'Callaghan Claire C Moustafa Ahmed A AA de Wit Sanne S Shine James M JM Robbins Trevor W TW Lewis Simon J G SJ Hornberger Michael M

Frontiers in computational neuroscience 20131212

Discrimination learning deficits in Parkinson's disease (PD) have been well-established. Using both behavioral patient studies and computational approaches, these deficits have typically been attributed to dopamine imbalance across the basal ganglia. However, this explanation of impaired learning in PD does not account for the possible contribution of other pathological changes that occur in the disease process, importantly including gray matter loss. To address this gap in the literature, the c ...[more]

PMID: 24376416

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Project description:ObjectiveThis prospective investigation examined: 1) processing speed and working memory relative to other cognitive domains in non-demented medically managed idiopathic Parkinson's disease, and 2) the predictive role of cortical/subcortical gray thickness/volume and white matter fractional anisotropy on processing speed and working memory.MethodsParticipants completed a neuropsychological protocol, Unified Parkinson's Disease Rating Scale, brain MRI, and fasting blood draw to rule out vascular contributors. Within group a priori anatomical contributors included bilateral frontal thickness, caudate nuclei volume, and prefrontal white matter fractional anisotropy.ResultsIdiopathic Parkinson's disease (n = 40; Hoehn & Yahr stages 1-3) and non-Parkinson's disease 'control' peers (n = 40) matched on demographics, general cognition, comorbidity, and imaging/blood vascular metrics. Cognitively, individuals with Parkinson's disease were significantly more impaired than controls on tests of processing speed, secondary deficits on working memory, with subtle impairments in memory, abstract reasoning, and visuoperceptual/spatial abilities. Anatomically, Parkinson's disease individuals were not statistically different in cortical gray thickness or subcortical gray volumes with the exception of the putamen. Tract Based Spatial Statistics showed reduced prefrontal fractional anisotropy for Parkinson's disease relative to controls. Within Parkinson's disease, prefrontal fractional anisotropy and caudate nucleus volume partially explained processing speed. For controls, only prefrontal white matter was a significant contributor to processing speed. There were no significant anatomical predictors of working memory for either group.ConclusionsCaudate nuclei volume and prefrontal fractional anisotropy, not frontal gray matter thickness, showed unique and combined significance for processing speed in Parkinson's disease. Findings underscore the relevance for examining gray-white matter interactions and also highlight clinical processing speed metrics as potential indicators of early cognitive impairment in PD.

Project description:BackgroundSelective loss of dopaminergic neurons and diminished putamen gray matter volume (GMV) represents a central feature of Parkinson's disease (PD). Recent studies have reported specific effects of kinectin 1 gene (KTN1) variants on the putamen GMV.ObjectiveTo examine the relationship of KTN1 variants, KTN1 mRNA expression in the putamen and substantia nigra pars compacta (SNc), putamen GMV, and PD.MethodsWe examined the associations between PD and a total of 1847 imputed KTN1 single nucleotide polymorphisms (SNPs) in one discovery sample [2,000 subjects with PD vs. 1,986 healthy controls (HC)], and confirmed the nominally significant associations (p < 0.05) in two replication samples (900 PD vs. 867 HC, and 940 PD vs. 801 HC, respectively). The regulatory effects of risk variants on the KTN1 mRNA expression in putamen and SNc and the putamen GMV were tested. We also quantified the expression levels of KTN1 mRNA in the putamen and/or SNc for comparison between PD and HC in five independent cohorts.ResultsSix replicable and two non-replicable KTN1-PD associations were identified (0.009 ≤ p ≤ 0.049). The major alleles of five SNPs, including rs12880292, rs8017172, rs17253792, rs945270, and rs4144657, significantly increased risk for PD (0.020 ≤ p ≤ 0.049) and putamen GMVs (19.08 ≤ β ≤ 60.38; 2.82 ≤ Z ≤ 15.03; 5.0 × 10-51 ≤ p ≤ 0.018). The risk alleles of five SNPs, including rs8017172, rs17253792, rs945270, rs4144657, and rs1188184 also significantly increased the KTN1 mRNA expression in the putamen or SNc (0.021 ≤ p ≤ 0.046). The KTN1 mRNA was abundant in the putamen and/or SNc across five independent cohorts and differentially expressed in the SNc between PD and HC in one cohort (p = 0.047).ConclusionThere was a consistent, significant, replicable, and robust positive relationship among the KTN1 variants, PD risk, KTN1 mRNA expression in putamen, and putamen volumes, and a modest relation between PD risk and KTN1 mRNA expression in SNc, suggesting that KTN1 may play a functional role in the development of PD.

Dataset Information

Fronto-striatal gray matter contributions to discrimination learning in Parkinson's disease.

Publications

Fronto-striatal gray matter contributions to discrimination learning in Parkinson's disease.

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