Abstract
Parkinson’s disease (PD) is a neurodegenerative disorder, characterised by cognitive decline and attentional impairment. Recently, variation in CHRNA4 (rs1044396) has been shown to affect visual and auditory function, affecting speed and attention, in healthy adults. An association between CHRNA4 variation and PD has not been shown. To determine the link between CHRNA4 variation and attentional deficit in PD. A genotype-phenotype correlation between the common CHRNA4:rs1044396 variant and several baseline parameters of attention was carried out in a large cohort of PD cases (n = 222) and controls (n = 159). We identified significant associations to measures of attention in PD patients compared to controls. However, we found no significant link to CHRNA4:rs1044396 genotypes to baseline attention variables in PD or in controls. We conclude that CHRNA4:rs1044396 genotypes do not significantly influence the attentional deficit found in PD patients. Contrary to previous studies, we also found no significant influence in healthy age-matched controls.
Keywords: Parkinson’s disease, Ageing, Cholinergic receptor, Attention
It is generally well known that many of our cognitive and perceptual functions decline as we age [9], however the extent of the age-related decline and the intra-individual variability remains unclear.
The role of acetylcholine in cognitive function is well documented and recent work indicates that variation in the gene CHRNA4 (a member of the family of nicotinic acetylcholine receptors) may modulate attention and spatial scaling performance in humans [4,5]. More specifically, a single nucleotide polymorphism in the CHRNA4 gene (rs1044396) appears to have an effect on visual and auditory function, affecting speed and attention, in healthy adults [7].
Parkinson’s disease (PD) is a neurodegenerative disorder characterised by a loss of midbrain dopaminergic (DA) neurons in the substantia nigra pars compacta. The aetiology of PD is likely caused by a complex combination of genetic and environmental factors. Cognitive decline, including attentional impairment, is a hallmark of both demented and non-demented PD cases. Convergent evidence from therapeutic intervention, neuroimaging and neuropathology studies in PD implicate degeneration of the subcortical cholinergic system in mediating attentional and executive dysfunction [2,10,11]. With this in mind, we examined the genetic effects of the CHRNA4 polymorphism; rs1044396; on a range on neuropsychological measures, including attention, in a well characterised cohort of PD patients. We hypothesised that this polymorphism might have functional effects upon attention in PD.
We compared 222 community based cases with PD fulfilling UK-PD Society brain bank criteria for the diagnosis of PD [6] (mean age 71.41 years, SD = 8.04, 61% male) from the north east of England to an ethnically age and gender matched control group (N = 159, mean age 69.69 years, SD = 7.88, 46% male), with no clinical evidence of PD. All were of Caucasian origin. Four PD patients were taking a cholinesterase inhibitor and none were taking modafinil.
At baseline, all subjects underwent cognitive assessment, including the mini-mental state examination (MMSE) [8]. At baseline and follow-up, all subjects underwent Cognitive Drug Research (CDR, Goring-on-Thames, UK) computer based attentional tasks that included assessment of power of attention (PoA), continuity of attention (CoA), cognitive reaction time (CRT) and cognitive fluctuation (PowCV) [1], where higher scores represent worse attentional performance and directly reflect the ability to maintain concentration to a particular task [1,3]. Full ethical approval was gained for this work and informed consent obtained from all participants.
All subjects, 222 cases and 159 controls were genotyped for the CHRNA4 polymorphism – rs1044396. Genotyping was done by primer extension of allele-specific extensions products by matrix-associated laser desorption/ionisation time-of-flight (MALDI-TOF, Seqeunom, San Diego, CA, USA) mass spectrometry. Genotypes were confirmed in 10% of random samples, by direct sequencing using an ABI3100 Genetic Analyser (Applied Biosystems).
Allele and genotype frequencies were compared using Pearson’s χ2 test. Multiple logistic regression was performed to look for interactions between the variables. All analyses were carried out using SPSS software version 17.0 (SPSS Inc.).
Comparisons of cognitive assessment between PD cases and controls revealed significant differences in MMSE, PoA and CoA (P = 1.2 × 10−9, 1.7 × 10−9 and 5.3 × 10−9, respectively, Table 1). There was no significant difference between PD patient CRT or PowCV when compared to controls (P = 0.737 and 0.146, respectively, Table 1).
Table 1.
Analysis of PD status and mean baseline variables (where; SD is standard deviation of the mean; P is Pearson’s probability; PD is PD cases; Con is controls. MMSE is Mini-Mental State Examination; PoA is power of attention; CoA is continuity of attention; CRT is cognitive reaction time).
| Variable | Mean score (SD) |
P | |
|---|---|---|---|
| PD | Con | ||
| MMSE | 25.6 (2.2) | 27.6 (3.8) | 1.2×10−9 |
| PoA | 1569 (363) | 1348 (183) | 1.7×10−9 |
| CoA | 63.0 (11.1) | 69.5 (4.9) | 5.3×10−9 |
| CRT | 160.0 (139) | 164.8 (81) | 0.737 |
| PowCV | 59.08 (12.6) | 54.12 (16.1) | 0.146 |
CHNRA4:rs1044396 genotyping revealed no direct relationship to the onset of PD, when comparing genotypes or alleles (Pearson’s P = 0.558 and P = 0.532, respectively, Table 2).
Table 2.
Analysis of PD status and CHRNA4:rs1044396 genotypes (where; PD is PD cases; Con is controls and P is Pearson’s probability and P* is Fisher’s probability).
| Group | Frequency |
P | ||
|---|---|---|---|---|
| CC | CT | TT | ||
| PD | 38 | 87 | 97 | 0.558 |
| Con | 21 | 63 | 75 | |
| Group | Frequency |
P* | |
|---|---|---|---|
| CC:CT | TT | ||
| PD | 125 | 97 | 0.532 |
| Con | 84 | 75 | |
| Group | Frequency |
P* | |
|---|---|---|---|
| C | T | ||
| PD | 163 | 281 | 0.317 |
| Con | 105 | 213 | |
When comparing mean baseline variables to CHRNA4:rs1044396 genotypes we found no significant associations with MMSE, PoA, and CoA scores in cases or controls (Table 3). However, we did find a significant difference in the mean CRT scores of PD patients when compared to CHRNA4:rs1044396 genotype (P = 0.040, Table 3) and the mean PowCV scores of controls when compared to CHRNA4:rs1044396 genotype (P = 0.038, Table 3), although correcting for multiple testing removed the statistical significance of these observations. There also appeared to be a trend towards lower CoA scores when the cohort was combined, although the P value did not reach significance (P = 0.072, Table 3).
Table 3.
Analysis of CHRNA4:rs1044396 on mean baseline variables (where; SD is standard deviation of the mean; P is ANOVA probability; PD is PD cases; Con is controls and Comb. is PD + Con. MMSE is Mini-Mental State Examination; PoA is power of attention; CoA is continuity of attention; CRT is cognitive reaction time).
| Variable | rs1044396 | Mean (SD) |
P | |||
|---|---|---|---|---|---|---|
| CC | CT | TT | ||||
| MMSE | CC v CT v TT | PD | 24.74 (4.3) | 26.20 (3.5) | 26.05 (3.2) | 0.111 |
| Con | 28.14 (2.2) | 27.87 (2.3) | 27.44 (2.2) | 0.353 | ||
| Comb. | 26.02 (4.0) | 26.92 (3.2) | 26.68 (2.9) | 0.207 | ||
| PoA | CC v CT v TT | PD | 1602 (502) | 1582 (351) | 1503 (264) | 0.201 |
| Con | 1420 (236) | 1326 (167) | 1350 (184) | 0.211 | ||
| Comb. | 1545 (442) | 1483 (319) | 1450 (249) | 0.180 | ||
| CoA | CC v CT v TT | PD | 60.7 (14.5) | 64.3 (9.1) | 63.9 (10.1) | 0.227 |
| Con | 67.8 (5.7) | 70.0 (5.2) | 69.6 (4.1) | 0.310 | ||
| Comb. | 62.9 (12.8) | 66.5 (8.3) | 65.9 (9.0) | 0.072 | ||
| CRT | CC v CT v TT | PD | 117.5 (206) | 160.3 (124) | 186.8 (119) | 0.040 |
| Con | 184.9 (83.0) | 164.2 (78.7) | 156.6 (83.7) | 0.486 | ||
| Comb. | 138.3 (180) | 161.8 (109) | 176.5 (109) | 0.152 | ||
| PowCV | CC v CT v TT | PD | 53.35 (6.4) | 62.24 (15.8) | 57.19 (17.3) | 0.273 |
| Con | 64.66 (10.7) | 52.43 (13.85) | 52.76 (10.49) | 0.038 | ||
| Comb. | 59.38 (10.4) | 57.74 (15.6) | 55.23 (14.7) | 0.501 | ||
As previous studies have shown that the CHRNA4:rs1044396 genotype TT has the strongest effect on attention [7], we performed analysis of CC:CT versus TT genotypes on baseline variables (Table 4). Tests of association did not reveal any link between the CC:CT or TT genotype with MMSE, PoA or CoA; however there was a significant association with CRT and TT homozygous PD patients (P = 0.043, Table 4), again not reaching significance after correcting for multiple significance testing. The previously identified association between PowCV scores and controls was improved when comparing CC:CT versus TT genotypes (P = 0.010, Table 4), although this would not reach significance after correction for multiple significance testing.
Table 4.
Analysis of combined CC:CT versus TT rs1044396 genotypes on mean baseline variables (where; SD is standard deviation of the mean; P is T-test probability; PD is PD cases; Con is controls and Comb. is PD + Con. MMSE is Mini-Mental State Examination; PoA is power of attention; CoA is continuity of attention; CRT is cognitive reaction time).
| Variable | rs1044396 | Mean (SD) |
P | ||
|---|---|---|---|---|---|
| CC:CT | TT | ||||
| MMSE | CC:CT v TT | PD | 25.77 (3.8) | 26.0 (3.2) | 0.575 |
| Con | 27.94 (2.2) | 27.44 (2.3) | 0.168 | ||
| Comb. | 26.68 (3.4) | 26.68 (2.9) | 0.990 | ||
| PoA | CC:CT v TT | PD | 1588.5 (400) | 1503.1 (264) | 0.077 |
| Con | 1348.8 (188) | 1350.9 (184) | 0.952 | ||
| Comb. | 1500.8 (357) | 1450.9 (249) | 0.157 | ||
| CoA | CC:CT v TT | PD | 63.2 (11.1) | 63.9 (10.1) | 0.640 |
| Con | 69.5 (5.3) | 69.6 (4.1) | 0.910 | ||
| Comb. | 65.5 (9.0) | 65.8 (9.0) | 0.744 | ||
| CRT | CC:CT v TT | PD | 147.4 (154) | 186.8 (119.3) | 0.043 |
| Con | 169.1 (79.6) | 156.7 (83.7) | 0.417 | ||
| Comb. | 155.2 (132.7) | 176.5 (109.0) | 0.121 | ||
| PowCV | CC:CT v TT | PD | 60.6 (14.9) | 57.2 (17.4) | 0.457 |
| Con | 55.4 (14.1) | 52.7 (10.5) | 0.010 | ||
| Comb. | 58.1 (14.7) | 55.2 (14.79) | 0.447 | ||
As previous studies have shown a link to TT-homozygotes and cognitive decline, which may evolve to dementia [7], we compared a subset of our subjects (143 PD cases and 96 age and gender matched controls) who had been evaluated for dementia on the basis of DSM-IV assessment and a MMSE ≤ 26. We found no significant association between CHRNA4:rs1044396 genotypes and the presence of dementia, however (Table 5).
Table 5.
Analysis of combined CC:CT versus TT rs1044396 genotypes on the presence of PD with dementia (where; SD is standard deviation of the mean; P is Pearson’s probability and P* is Fisher’s probability; PD is PD cases; Con is controls).
| Dementia | Frequency |
P | |||
|---|---|---|---|---|---|
| CC | CT | TT | |||
| PD | Y | 11 | 13 | 25 | 0.205 |
| N | 18 | 39 | 37 | ||
| Con | Y | 1 | 6 | 8 | 0.697 |
| N | 12 | 29 | 40 | ||
| Dementia | Frequency |
P* | ||
|---|---|---|---|---|
| CC:CT | TT | |||
| PD | Y | 24 | 25 | 0.214 |
| N | 57 | 37 | ||
| Con | Y | 7 | 8 | 1.000 |
| N | 41 | 40 | ||
Multiple logistic regression analysis did not reveal any additional significant results after correction for multiple significance testing.
The results indicate that CHRNA4:rs1044396 genotypes do not have a strong effect on attention, and its progression to dementia, in PD. Previous work has shown that the rs1044396 TT allele has an adverse effect on the ability of healthy individuals to perform complex attention tasks [7]. Whilst an association with cognitive decline (and attention) is evident in PD, a possible reason for our lack of CHRNA4 genetic association could be the younger mean age of our study group. Alternatively, the effects of medication could mask a possible genetic effect in the PD group. There was no evidence of an association between attention and levodopa equivalents dose after correction for multiple significance testing, however, and only four patients were taking cholinomimetic drugs.
Reinvang et al. (2009) found their most striking effect was in patients aged 70–79 years [7]. Another potential confounding, and perhaps more likely, factor may be PD disease progression itself. If the effect of CHRNA4 genotype on attention is weak in healthy individuals, then it may be masked in a PD cohort whose attention capacity is already markedly reduced due to disease itself or its treatment. It is interesting perhaps that we did not see significant evidence of attention decline in controls, although this may reflect the size of our study. It is conceivable that a larger study of similar design might reveal subtle differences between the groups.
Acknowledgements
P.F.C. is a Wellcome Trust Senior Fellow in Clinical Science. This work was supported by an NIHR Biomedical Research Centre for Ageing and Age-related Disease Award to the Newcastle upon Tyne Foundation Hospitals NHS Trust. We also acknowledge generous support from the Newcastle University Lockhart Parkinson’s Disease Fund.
References
- [1].Ballard CG, Stephens S, McLaren A, Wesnes K, Kenny RA, Burton E, O’Brien J, Kalaria R. Neuropsychological deficits in older stroke patients. Ann. N. Y. Acad. Sci. 2002;977:179–182. doi: 10.1111/j.1749-6632.2002.tb04815.x. [DOI] [PubMed] [Google Scholar]
- [2].Bohnen NI, Kaufer DI, Hendrickson R, Ivanco LS, Lopresti BJ, Constantine GM, Mathis CA, Davis JG, Moore RY, Dekosky ST. Cognitive correlates of cortical cholinergic denervation in Parkinson’s disease and parkinsonian dementia. J. Neurol. 2006;253:242–247. doi: 10.1007/s00415-005-0971-0. [DOI] [PubMed] [Google Scholar]
- [3].Emre M, Aarsland D, Albanese A, Byrne EJ, Deuschl G, De Deyn PP, Durif F, Kulisevsky J, van Laar T, Lees A, Poewe W, Robillard A, Rosa MM, Wolters EC, Quarg P, Tekin S, Lane R. Rivastigmine for dementia associated with Parkinson’s disease. N. Engl. J. Med. 2004;351:2509–2518. doi: 10.1056/NEJMoa041470. [DOI] [PubMed] [Google Scholar]
- [4].Espeseth T, Greenwood PM, Reinvang I, Fjell AM, Walhovd KB, Westlye LT, Wehling E, Lundervold A, Rootwelt H, Parasuraman R. Interactive effects of APOE and CHRNA4 on attention and white matter volume in healthy middle-aged and older adults. Cogn. Affect Behav. Neurosci. 2006;6:31–43. doi: 10.3758/cabn.6.1.31. [DOI] [PubMed] [Google Scholar]
- [5].Greenwood PM, Fossella JA, Parasuraman R. Specificity of the effect of a nicotinic receptor polymorphism on individual differences in visuospatial attention. J. Cogn. Neurosci. 2005;17:1611–1620. doi: 10.1162/089892905774597281. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Hughes AJ, Colosimo C, Kleedorfer B, Daniel SE, Lees AJ. The dopaminergic response in multiple system atrophy. J Neurol Neurosurg Psychiatry. 1992;55:1009–1013. doi: 10.1136/jnnp.55.11.1009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Reinvang I, Lundervold AJ, Rootwelt H, Wehling E, Espeseth T. Individual variation in a cholinergic receptor gene modulates attention. Neurosci. Lett. 2009;453:131–134. doi: 10.1016/j.neulet.2009.02.029. [DOI] [PubMed] [Google Scholar]
- [8].Roth M, Tym E, Mountjoy CQ, Huppert FA, Hendrie H, Verma S, Goddard R, CAMDEX A standardised instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia. Br. J. Psychiatry. 1986;149:698–709. doi: 10.1192/bjp.149.6.698. [DOI] [PubMed] [Google Scholar]
- [9].Salthouse TA. The processing-speed theory of adult age differences in cognition. Psychol. Rev. 1996;103:403–428. doi: 10.1037/0033-295x.103.3.403. [DOI] [PubMed] [Google Scholar]
- [10].Tiraboschi P, Hansen LA, Alford M, Sabbagh MN, Schoos B, Masliah E, Thal LJ, Corey-Bloom J. Cholinergic dysfunction in diseases with Lewy bodies. Neurology. 2000;54:407–411. doi: 10.1212/wnl.54.2.407. [DOI] [PubMed] [Google Scholar]
- [11].Wesnes KA, McKeith I, Edgar C, Emre M, Lane R. Benefits of rivastigmine on attention in dementia associated with Parkinson disease. Neurology. 2005;65:1654–1656. doi: 10.1212/01.wnl.0000184517.69816.e9. [DOI] [PubMed] [Google Scholar]