Influence of serotonin transporter gene polymorphisms on ... - Nature

Molecular Psychiatry (2005) 10, 1133–1139 & 2005 Nature Publishing Group All rights reserved 1359-4184/05 $30.00 www.nature.com/mp

ORIGINAL RESEARCH ARTICLE

Influence of serotonin transporter gene polymorphisms on cognitive decline and cognitive abilities in a nondemented elderly population A Payton1, L Gibbons2, Y Davidson2, W Ollier1, P Rabbitt3, J Worthington1, A Pickles4, N Pendleton2 and M Horan2 1

Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK; 2Clinical Gerontology, University of Manchester, Clinical Sciences Building, Hope Hospital, Salford, Greater Manchester, UK; 3Age & Cognitive Performance Research Centre, University of Manchester, Manchester, UK; 4Biostatistics Group, University of Manchester, Manchester, UK Dysfunction of the serotonergic pathway disrupts normal cognitive functioning and is believed to be the underlying basis for a variety of psychiatric disorders. Two functional polymorphisms within the serotonin transporter (SLC6A4) gene (promoter 44 bp insertion/deletion (HTTLPR) and an intron two 16 or 17 bp variable number tandem repeat (VNTR2)) have been extensively studied in psychiatric conditions but not in the cognitive functioning of normal individuals. We have investigated these two polymorphisms for association with both the level of cognitive abilities and their decline with age using a cohort consisting of over 750 elderly nondemented individuals with a follow-up of up to 15 years. We found that volunteers homozygous for the VNTR2 12 allele had a faster rate of decline for all cognitive tests. This reached significance for both tests of fluid intelligence (novel problem solving) (AH1 P ¼ 0.002, AH2 P ¼ 0.014), the test of semantic memory (P ¼ 0.010) and general cognitive ability (P ¼ 0.006). No association was observed between the HTTLPR polymorphism and the rate of cognitive decline when analysed either independently or in combination with the VNTR2 polymorphism based on their influence on expression in vitro. No associations were observed between the two polymorphisms and the baseline level of cognitive abilities. This is only the second gene that has been reported to regulate the rate of cognitive decline in nondemented individuals and may be a target for the treatment of cognitive impairment in the elderly. Molecular Psychiatry (2005) 10, 1133–1139. doi:10.1038/sj.mp.4001733; published online 16 August 2005 Keywords: serotonin transporter; polymorphism; cognition; memory; genes; association

In an increasingly long-lived population severe cognitive impairment, caused by either the normal ageing process or dementia, is an escalating problem that currently has no effective treatment. Cognitive ability and its rate of decline are highly heritable and both have been shown to predict dementia onset.1–4 Of the 13 quantitative trait loci (QTL) currently associated with the level of cognitive ability in normal individuals the most widely reported are located in genes involved in synaptic transmission.5 These comprise the adrenergic receptor 2A, catecholO-methyltransferase, dopamine receptor D2, cholinergic muscarinic 2 receptor, brain-derived neurotrophic factor, metabotrophic glutamate receptor 3 and the serotonin receptor 2A.6–13 To date only the

Correspondence: Dr A Payton, Centre for Integrated Genomic Medical Research, University of Manchester, Stopford building, Oxford road, Manchester M13 9PT, UK. E-mail: [email protected] Received 28 February 2005; revised 6 July 2005; accepted 19 July 2005; published online 16 August 2005

apolipoprotein E e4 allele has been associated with cognitive decline in nondemented individuals and this finding has been challenged.14–19 Serotonin has been shown to play a role in brain development and cognitive functioning.20,21 There is also a decrease in total brain serotonin with age that may predispose the elderly to depression, dementia and cognitive dysfunction.22 Despite the importance of serotonin as a modulator of memory and learning the influence of two functional polymorphisms (HTTLPR and VNTR2) in the SLC6A4 gene, which codes for a protein responsible for the reuptake of serotonin, have not been investigated in the field of cognitive genetics. In contrast, there has been considerable focus on this gene in psychiatric disorders. An early association study reported that the SLC6A4 HTTLPR polymorphism predisposes to neurosis.23 Since then, many more groups have examined this gene in other behavioural disorders including anxiety-related traits, suicide, bipolar mood disorder, attention deficit hyperactivity disorder, impulsive aggressive behaviour and psychoticism.24–29 Unfortu-

Influence of serotonin transporter gene polymorphisms A Payton et al

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nately, inconsistencies within the literature, probably largely due to the use of inadequate sample size, have been a common problem in these studies. For example, of the 22 publications investigating association between the HTTLPR polymorphism and neurosis only four have reported an association.30 The use of meta-analysis and large primary association studies has helped address the power issue and several recent publications have provided more conclusive evidence that the HTTLPR polymorphism is associated with suicidal behaviour and alcoholism.25,31 However, several large statistically powerful studies have still produced conflicting reports regarding the role of the promoter polymorphism in affective disorders and neuroticism.24,30,32,33 Both polymorphisms in SLC6A4 have been shown to be functional in vitro. The HTTLPR insertion has been shown to reduce transcriptional efficiency, while the VNTR2 polymorphism, which has two common variants (10 and 12 16/17 bp repeats), influences enhancer activity.34–36 It has recently been shown using lymphoblast cell lines that both polymorphisms regulate transcription in an allele-dependent manner.37 Analysing these polymorphisms in combination allows potentially high-expression individuals (those with two high expression loci) to be compared against low-expression individuals (those with two low-expression loci) and those who carry one high- and one low-expression loci. To our knowledge analysing these polymorphisms in combination according to their effect on expression has not been used in any association studies examining the SLC6A4 gene. The influence of these polymorphisms in vivo is unknown.

Methods Study group The 758 elderly Caucasian volunteers involved in this study form part of the Dyne Steele DNA bank for cognitive genetic studies and comprise 234 males and 524 females. On entry to the study the age range was 50-85 years and the mean age was 63 years. Data were available for the potential confounders of hypertension, diabetes and depression for 705, 703 and 500 volunteers, respectively. Of these 283 individuals had hypertension and 38 were diabetic. Depression was assessed using the Geriatric Depression Scale, which is a continuous variable. Volunteers undertook cognitive tests that were administered at five yearly intervals with a follow-up of up to 15 years. At the final year of testing (fourth time point) data were available for 116 males and 295 females. Tests of fluid intelligence comprised the Heim intelligence tests parts one and two (AH and AH2).38 Vocabulary ability was measured using the Raven Mill Hill vocabulary scale part A (MHA).39 Processing speed was assessed using the Random Letters (RL) test. A series of memory tests measured semantic memory (SEM), Immediate verbal Recall (IR), Delayed verbal Recall (DR) and Spatial Recall (SR). Molecular Psychiatry

At the beginning of the study all volunteers achieved maximum score on the mini mental state examination, and at the time of venesection (11–15 years later), cognitive tests indicated no sign of dementia. Extensive data on demographics and health have also been archived. Details on the recruitment, composition, selective attrition and cognitive tests are described in detail elsewhere.40 Volunteers gave written consent for the use of their DNA in the investigations performed. Genotyping All PCR reactions were carried out in 96-well microtitre plates using NH4 buffer (Bioline), 1.5 mM MgCl2, 0.1 mM dNTP’s, 0.2 U Taq polymerase (Bioline, BioTaq), 10 pmol of each primer, 0.5 M Betaine and 10 ng of genomic DNA with a final reaction volume of 10 ml. Cycle conditions: 35 cycles at 951C for 40 s, annealing temperature 611C for 30 s, 721C for 30 s followed by 5 min at 721C using a PTC-225 Peltier Thermal Cycler (MJ Research). PCR product was separated on a 3% agarose gel and visualised under ultra violet. HTTLPR polymorphism: oligonucleotide primers: forward 50 GGC GTT GCC GCT CTG AAT GC; reverse 50 GAG GGA CTG AGC TGG ACA ACC AC. Insertion/deletion produces band sizes of 528 and 484 bp, respectively.41 VNTR2: oligonucleotides primers: forward 50 GTC AGT ATC ACA GGC TGC GAG and reverse 50 TGT TCC TAG TCT TAC GCC AGT G. Three alleles containing nine, 10 and 12 copies of the VNTR produced band sizes of 166, 183 and 200 bp, respectively.42 Statistical analysis Least-squares multiple regression analysis was performed in Stata (2001) to determine cross-sectional associations of cognitive ability scores obtained on entry to the study with genotype frequency. Test scores were normally distributed. Dominant common factors were identified and scores extracted for both the eight baseline measures used in the crosssectional analysis (Table 2) (first eignevalue 3.10, second eigenvalue 0.68) and the seven measures used in the longitudinal analysis (Table 3) (first eignevalue 2.80, second eigenvalue 0.64). To investigate factors predictive of cognitive decline we used a marginal regression model with an estimator of the parameter covariance matrix that was robust to the correlation among repeated observations.43 An independence working model was chosen since this allowed the use of nonresponse weights that were a function of previously observed cognitive scores, and thus could be used to check for the effects of selective attrition.44 In addition to linear trend terms the models also included dummy variables to account for practice effects, previously shown to be important in these data.45 The statistical significance of terms in the regressions were obtained from adjusted Wald’s tests. As vocabulary ability tends to remain relatively stable with age, longitudinal analysis was not performed on the MHA test.40


Data were adjusted for age and gender by covarying their effects. The comorbid medical disorders of hypertension, diabetes and depression were investigated as potential confounders. No correction was made for multiple testing because the majority of cognitive tests were moderately/highly correlated (Table 1) and moderate linkage disequilibrium existed between the two polymorphisms.

tion was observed between those who were HTTLPR homozygous 10 and homozygous 12 for the delayed recall test. Adjusting for hypertension, diabetes and depression had no discernable impact on the levels of significance. No associations were observed when the polymorphisms were analysed according to their postulated influence on expression.

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Discussion Results HTTLPR allele frequencies were identical to those previously reported in a control population (0.57 (insertion) and 0.43 (deletion)).41 VNTR2 had three alleles comprised of nine, 10 and 12 16/17 base pair repeats with frequencies of 0.02, 0.39 and 0.59, respectively. This is similar to control frequencies previously reported (0.01, 0.40 and 0.59, respectively).42 All genotypes were in Hardy–Weinberg equilibrium. Weak linkage disequilibrium existed between the polymorphisms with an LD correlation of D0 ¼ 0.35 (Table 1). Longitudinal analysis found that individuals homozygous for the VNTR2 12 alleles had a faster rate of cognitive decline for all cognitive tests compared with heterozygous or homozygous 10 individuals (Table 3). This reached significance for both tests of fluid intelligence (AH1 P ¼ 0.002, AH2 P ¼ 0.014), the test of SEM (P ¼ 0.010) and general cognitive ability (P ¼ 0.006). Other memory measures showed nonsignificant trends (IR P ¼ 0.15, DR P ¼ 0.087 and SR P ¼ 0.060). No associations were observed between the HTTLPR polymorphism and cognitive decline. Weighting to account for selective attrition had no material impact on the longitudinal results. Crosssectional analysis revealed no association between the level of any cognitive abilities and the SLC6A4 polymorphisms with the exception of heterozygous HTTLPR individuals who scored significantly higher on the delayed recall test compared to homozygous 12 volunteers (P ¼ 0.035) (Table 2). However, no associa-

Table 1

AH1

AH2 RL MHA IR DR SEM SR

Correlation values of cognitive tests

AH1

AH2

RL

MHA

IR

DR

SEM

SR

1.00 0.75 0.45 0.61 0.31 0.32 0.38 0.29

1.00 0.49 0.43 0.23 0.28 0.31 0.29

1.00 0.23 0.21 0.27 0.24 0.21

1.00 0.18 0.25 0.31 0.15

1.00 0.64 0.39 0.23

1.00 0.46 0.34

1.00 0.29

1.00

AH1 and AH2: Heim intelligence tests parts 1 and 2 (measures of fluid Intelligence); RL: random letter test (measures of processing speed); MHA: Mill Hill vocabulary test part A (measures of vocabulary ability); IR: immediate verbal recall; DR: delayed recall; SEM: semantic memory; SR: spatial recall (measures of memory).

Our results suggest that the SLC6A4 VNTR2 polymorphism but not the HTTLPR polymorphism regulates the rate of cognitive decline in an elderly population. For all cognitive tests VNTR2 homozygous 12 volunteers declined faster than heterozygous or homozygous 10 individuals. Based on the findings for the common factor, these effects would correspond, respectively, to relative losses of 2.9 and 4.4 IQ points over a 10-year period. The 4.4 IQ effect size of the VNTR2 homozygous 12 genotype towards the total variance of cognitive decline can be given perspective by comparing it to the effect size caused by ‘normal ageing’ which is the biggest risk factor for cognitive decline in healthy individuals. Based on our statistical model with a negative quadratic age coefficient, general cognitive ability is predicted to fall at a rate of 6.3 IQ points over a 10-year period. The VNTR2 12 allele has been shown to increase transporter expression, which would result in an increased rate of serotonin reuptake and consequently less available serotonin for receptor binding.37 In the ageing brain, which has increasingly reduced total serotonin levels possibly as a result of an age-related increase in monoamine oxidase and/or an increase in oxidative stress, the additional synaptic depletion of serotonin may be responsible for the faster rate of decline.22,46 The promoter polymorphism had no influence on decline when analysed either independently or in combination with the intronic VNTR. This was surprising given that both polymorphisms have been shown to regulate expression. However, the expression studies were conducted using in vitro techniques and the function of these polymorphisms in vivo in an ageing brain is unknown.37,47 It was also observed that the VNTR2 polymorphism affected the rate of decline in a domain-specific manner. The influence of the polymorphism was strongest for tests of fluid intelligence compared to tests of memory and processing speed. This apparent domain specificity may be an artefact of differential brain ageing. Previous work by our group has shown that tests of fluid intelligence decline at a faster and accelerated rate in normal elderly individuals compared to memory tests, which declined at a slower and linear rate.40 In addition, work using mouse models has found that serotonin levels in aged mice are depleted to a greater extent in the cortex (implicated in fluid intelligence) (25% reduction) than the hippocampus (involved in memory) (16% reduction).46 It is therefore likely that the VNTR2 polymorphism has a stronger association with tests of Molecular Psychiatry


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Table 2 Test

Influence of the SLC6A4 polymorphisms on the level of cognitive abilities

VNTR

Fluid intelligence AH1 HTTLPR VNTR2 AH2 HTTLPR VNTR2

Max score

Mean score HWT

Mean score Het

P-value

65

37.4 36.6 35.2 34.6

36.6 37.3 33.7 34.2

0.787 0.553 0.285 0.672

1.874, 1.580, 2.346, 2.527,

65

95% CI

Mean score HM

P-value

95% CI

1.422 2.949 0.691 1.630

37.4 37.4 34.1 34.4

0.720 0.456 0.521 0.915

1.692, 1.468, 2.531, 2.292,

2.448 3.264 1.283 2.054

Vocabulary MHA HTTLPR VNTR2

33

24.0 24.0

24.2 24.0

0.358 0.953

0.362, 0.999 0.913, 0.970

24.3 24.5

0.349 0.307

0.446, 1.262 0.471, 1.496

Processing speed RL HTTLPR VNTR2

316

208.5 208.4

204.6 203.6

0.396 0.319

9.562, 3.788 13.900, 4.532

208.7 210.2

0.677 0.616

6.565, 10.104 7.131, 12.024

10

7.4 7.1 5.7 5.2 6.7 6.5 7.6 7.4

7.2 7.3 5.2 5.4 6.3 6.5 7.6 7.8

0.080 0.350 0.037 0.379 0.070 0.811 0.750 0.141

0.477, 0.182, 0.804, 0.298, 0.825, 0.523, 0.327, 0.135,

7.5 7.4 5.6 5.5 6.4 6.3 7.9 7.6

0.472 0.193 0.994 0.276 0.316 0.688 0.128 0.400

0.200, 0.121, 0.484, 0.249, 0.810, 0.747, 0.109, 0.322,

0.127 0.689

0.300, 0.037 0.185, 0.280

0.900 0.674

0.226, 0.199 0.190, 0.293

Memory IR DR SEM SR Common factor

HTTLPR VNTR2 HTTLPR VNTR2 HTTLPR VNTR2 HTTLPR VNTR2 HTTLPR VNTR2

10 15 12

0.027 0.512 0.026 0.780 0.032 0.669 0.453 0.950

0.430 0.599 0.487 0.871 0.261 0.493 0.865 0.805

Comparison of mean scores of heterozygous (Het) and homozygous mutant (HM) volunteers against homozygous wild-type (HWT) volunteers. Number of volunteers: HTTLPR HWT, Het, HM (229, 377, 148, respectively). VNTR2 HWT, Het, HM (238, 380, 111, respectively). AH1 and AH2: Heim intelligence tests parts 1 and 2; MHA: Mill Hill vocabulary tests part A; RL: random letter test; IR: immediate verbal recall; DR: delayed recall; SEM: semantic memory; SR: spatial recall.

fluid intelligence because they have a steeper trajectory with greater interindividual variation (which subsequently increases statistical power) and because preferential depletion of serotonin in the frontal cortex further reduces the amount of serotonin available for receptor binding. We also observed that the VNTR2 polymorphism was significantly associated with SEM but not verbal memory. SEM tends to decline at a much slower rate than other cognitive domains. However, changes are observed in the SEM network with age, in particular there is a decrease in left prefrontal cortex activation.48 Indeed, SEM was more closely correlated to fluid intelligence than verbal memory suggesting that they are more likely to share common biological pathways. The reasons for the differences in the rate of decline of specific cognitive domains is unknown but may be attributed to differences in the concentration of nonhaeme iron that catalyse free radicals and which tend to be at higher concentrations in the cortex, hippocampus, striatum and hypothalamus.49 Interestingly, the work conducted by Arivazhagan and Molecular Psychiatry

Panneerselvam46 found that intraperitoneal administration of the antioxidant DL-a-lipoic acid to aged mice returned the levels of serotonin to similar levels found in young mice. In addition, the administration of selective serotonin reuptake inhibitors has been shown to increase cognitive performance in nondemented individuals although these findings have been challenged.50,51 These results, together with work demonstrating that serotonin receptor agonists enhance cognitive performance, suggest that modulation of the serotonin pathway may be a potential mechanism of combating cognitive impairment in the elderly.52 No significant associations were observed between these polymorphisms and the level of cognitive abilities. This suggests that either the SLC6A4 polymorphisms have no influence on the level of cognitive ability or that the genetic contribution is too small for a cohort of 750 individuals to detect. Certainly, inconsistency within the literature is a hallmark of every association study that has investigated the genetics of complex diseases and traits


Table 3

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Influence of the SLC6A4 polymorphisms on cognitive decline

Test

Fluid intelligence AH1 AH2 Processing speed RL Memory IR DR SEM SR Common factor

VNTR

Heterozygous

Homozygous Del/12 alleles

Coefficient

P-value

95% CI

Coefficient

P-value

HTTLPR VNTR2 HTTLPR VNTR2

0.007 0.014 0.009 0.011

0.251 0.082 0.161 0.202

0.018, 0.029, 0.021, 0.027,

HTTLPR VNTR2

0.003 0.006

HTTLPR VNTR2 HTTLPR VNTR2 HTTLPR VNTR2 HTTLPR VNTR2

0.005 0.002 0.003 0.006

0.000 0.025 0.001 0.021

0.956 0.002 0.898 0.014

0.013, 0.042, 0.016, 0.038,

0.642 0.553

0.010, 0.017 0.014, 0.027

0.011 0.008

0.237 0.458

0.007, 0.028 0.029, 0.013

0.001 0.024 0.010 0.018 0.007 0.030 0.004 0.029

0.931 0.284 0.181 0.190 0.363 0.014 0.630 0.022

0.015, 0.068, 0.005, 0.044, 0.008, 0.054, 0.020, 0.053,

0.002 0.032 0.008 0.024 0.008 0.032 0.005 0.025

0.895 0.156 0.438 0.087 0.362 0.010 0.703 0.060

0.028, 0.078, 0.012, 0.051, 0.010, 0.056, 0.019, 0.050,

HTTLPR VNTR2

0.001 0.019

0.847 0.065

0.012, 0.014 0.040, 0.001

0.008 0.029

0.400 0.006

0.010, 0.026 0.050, 0.008

0.017 0.012 0.024 0.009 0.022 0.006 0.012 0.004

95% CI

0.013 0.009 0.014 0.004

0.032 0.012 0.028 0.003 0.028 0.008 0.028 0.001

Coefficient is the difference in the rate of decline per year (standard deviation units) between genotype groups. Differences in the rate of decline between genotype groups was calculated by comparing heterozygous/homozygous HTTLPR Del/VNTR2 12 volunteers against volunteers who were homozygous for the HTTLPR Ins/VNTR2 10 allele. VNTR: variable number tandem repeat; AH1 and AH2: Heim intelligence tests parts 1 and 2; RL: random letter test; IR: immediate verbal recall; DR: delayed recall; SEM: semantic memory; SR: spatial recall.

and inadequate power and is largely to blame.53 Implicated QTL’s typically contribute between 1 and 8% to the variation in cognitive ability. It has therefore been recommended that a study should have 80% power to detect QTLs that contribute 1% of the variance.54 Depending upon the alpha value, D0 and allele frequency this has been estimated at approximately 1000 individuals. With a sample size of 758 we had 99% power to detect a 4% variance with a stringent significance level of 0.001. Given that the majority of association studies investigating the serotonin transporter polymorphisms have used sample sizes of between 100 and 300 subjects it is unsurprising that conflicting results have been published. It is still however crucial that our results are replicated using an independent longitudinal cohort. Cognitive genetic research is a new rapidly expanding field that will provide a greater understanding of the biological mechanisms that regulate cognition and its decline with age. Our work is among the first to describe a gene that regulates cognitive decline and results such as these may help in the development of new and more efficient treatments designed to combat cognitive impairment in the elderly.

Acknowledgements This work was supported by the Wellcome Trust (Grant number GD045ERG). Blood collection and DNA extraction was partly funded by Research into Ageing.

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