Influence and interactions of cathepsin D, HLA-DRB1 and APOE on cognitive abilities in an older non-demented population
*A. Payton, Centre for Integrated Genomic Medical Research, Stopford building, University of Manchester, Oxford road, Manchester, UK. E-mail: firstname.lastname@example.org
Cathepsin D (CTSD), human leukocyte antigen DRB1 (HLA-DRB1) and apolipoprotein E (APOE) have all been associated with cognitive ability in both demented and non-demented individuals. CTSD is a pleiotrophic protein whose functions include the processing of proteins prior to presentation by HLA. Several studies have also reported that a functional exon 2 polymorphism in the CTSD gene interacts with APOEɛ4 resulting in an increased risk of developing Alzheimer's disease (AD). We have previously reported that the CTSD exon 2 polymorphism regulates fluid intelligence. In this study, we extend this finding to other cognitive domains and investigate interactions with APOE and HLA-DRB1. Using a cohort of 766 non-demented volunteers, we found that the CTSD exon 2 T allele was associated with a decrease in several cognitive domains that comprise processing speed [random letters (RLs) test, P = 0.012; alphabet-coding task (ACT), P = 0.001], spatial recall (SR) (P = 0.016) and an additional test of fluid intelligence (P = 0.010). We also observed that the HLA-DR1 was associated with enhanced cumulative recall ability (P = 0.006), and conversely HLA-DR5 was associated with diminished delayed verbal recall and SR abilities (P = 0.014 and P = 0.003, respectively). When analysed independently, APOEɛ4 did not influence any cognitive domains. In contrast, CTSD T/APOEɛ4-positive volunteers scored lower on tests of fluid intelligence (P = 0.015), processing speed (ACT, P = 0.001; RL, P = 0.013) and immediate recall (P = 0.029). Scores were lower for all these tests than when CTSD and APOE were analysed independently. This supports previous findings in AD that have also reported an epistatic interaction. In addition, we found that CTSD T/HLA-DR2-positive volunteers had reduced processing speed (ACT, P = 0.040; RL, P = 0.014) and had significantly lower cumulative and SR abilities (P = 0.003 and P = 0.001, respectively). Biological interaction between these two proteins has previously been shown where HLA-DR2 binds more readily to the myelin basic protein (MBP) compared with other DR antigens, preventing MBP cleavage by CTSD.
Cathepsin D (CTSD) is an aspartate lysosomal enzyme that is involved in the degradation of endocytosed and cellular proteins, apoptosis and brain development (Bidere et al. 2003; Nakanishi 2003; Tyynela et al. 2000). The gene contains a functional C>T (alanine to valine) transition within exon 2 that has been shown to reduce its intracellular maturation and increase secretion of pro-CTSD from the cell (Touitou et al. 1994). CTSD has also been shown to be important in Alzheimer's disease (AD)-related processes including the cleavage of amyloid precursor protein (APP) (McDermott & Gibson 1996; Sadik et al. 1999), degradation of tau (Bi et al. 2000) and regulation of β-amyloid levels (Papassotiropoulos et al. 2002). A recent meta-analysis study that combined data from 14 association studies reported that the CTSD T allele is not associated with AD risk once the initial report had been removed from the analysis (Ntais et al. 2004). However, the Ntais study did find that the CTSD T allele increased the risk of AD when in the presence of the APOEɛ4 allele. The association between apolipoprotein E (APOE) genotype and cognitive ability in individuals without dementia has produced conflicting results (Berr et al. 1996; Pendleton et al. 2002; Small et al. 2000). No studies until now have investigated possible epistatic interaction between the CTSD and APOE polymorphisms in elderly non-demented individuals.
Age-related changes in the brain white matter have been shown to have a role in cognitive impairment in both animal models and humans (Peters et al. 1996; Petkov et al. 2004). In particular, there is a loss of myelin and there are changes in oligodendrocyte proteins that are accompanied by an increase in microglia activation (Mattiace et al. 1990; Sloane et al. 1999). This activation involves the microglia gaining both phagocytotic capacity and the ability to express major histocompatibility complex (MHC) antigens (Dickson et al. 1991; Neumann 2001). The MHC is a highly polymorphic region located on the short arm of chromosome 6 that is responsible for presenting fragments of antigens to T cells, thereby eliciting an immune response (Dawkins et al. 1999). Three classes of molecules have been characterized within the MHC: class I region (HLA-A, -B and –C), class II region (HLA-DR, -DP and -DQ) and class III region (comprising over 60 genes). HLA antigens have been associated with cognitive functioning in a number of neurological diseases including AD (Alvarez et al. 2002; Ballerini et al. 1999; Neill et al. 1999; Payami et al. 1997) and multiple sclerosis (MS) (Barcellos et al. 2003; Guerini et al. 2003; Liblau & Gautam 2000; Weatherby et al. 2001). A role for HLA and cognitive ability in non-demented individuals has also been implicated (Shepherd et al. 2004). Although HLA and CTSD have been implicated in cognitive ability and it has been shown that CTSD processes antigen for HLA, this is the first study to investigate possible epistatic interactions between these two genes.
The 766 Caucasian volunteers involved in this study comprise 234 males and 532 females with an age range of 50–85 years and mean age of 62.9 years. Of these, 262 were diagnosed with hypertension and 31 were diagnosed with diabetes. This cohort forms part of the Dyne Steele DNA bank for cognitive genetic studies. On entry to 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, health and scores from cognitive tests have been archived. Tests of fluid intelligence comprised the Heim intelligence test parts one and two (Heim 1970). Vocabulary ability was measured using the Raven Mill Hill vocabulary scale parts A and B (Raven 1965). Processing speed was assessed using the alphabet-coding task (ACT) (Savage 1984) and the random letters (RLs) test. A series of memory tests measured semantic memory (SEM), immediate verbal recall (IR), delayed verbal recall (DR), cumulative recall (CR) and spatial recall (SR). Details on the recruitment, composition, selective attrition and cognitive tests are described in detail elsewhere (Rabbitt et al. 2004). Volunteers gave written consent for the use of their DNA in the investigations performed.
The CTSD exon 2 C>T transition was amplified using primers forward: 5′-GTG ACA GGC AGG AGT TTG GT-3′ and reverse: 5′-GGG CTA AGA CCT CAT ACT CAC G-3′. PCRs were carried out in 96-well microtitre plates with a final reaction volume of 20 µl containing NH4 buffer (Bioline, London, UK), 1.5 mm MgCl2, 0.1 mm dNTP's, 0.2 U Taq polymerase (Bioline, BioTaq, London, UK), 10 pmol of each primer, 50 ng of genomic DNA and 0.5 m Betaine. Cycle conditions: 35 cycles at 95 °C/40 s, 60 °C/30 s and 72 °C/30 s followed by 5 min at 72 °C using a PTC-225 Peltier Thermal Cycler (MJ Research, Cambridge, UK). The 343-bp product was digested overnight with MwoI (New England Biolabs, Hitchin, UK), and the fragments were separated on a 2% agarose gel. The C allele digested into two distinctive 168 and 82 bp bands, and the T allele formed a distinctive 250-bp band.
Codons 112 and 158 containing polymorphic nucleotides 3745 and 3883 within the APOE gene were amplified using primers forward: 5′-GCA CGG CTG TCC AAG GAG CTG GAG GC-3′ and reverse: 5′-GGC GCT CGC GGA TGG CGC TGA G-3′. PCRs were carried out as described for CTSD with the exception of the annealing temperature that was 67 °C. The 299-bp product was digested overnight with HhaI (New England Biolabs), and the fragments were separated on a 5% agarose gel. Alleles 2, 3 and 4 were identified by the presence of 91 + 83-bp, 91 + 48 + 35-bp and 72 + 48 + 35-bp fragments, respectively.
HLA genotyping was performed using a semi-automated commercial reverse hybridization method (Dynal Biotech, Wirral, UK). PCR was performed using 45-µl reactions that comprise 30-µl premade PCR master mix (biotinylated primers, dNTPs, Taq and KCL buffer) and 15-µl DNA (10 ng/µl).
Least squares multiple regression analysis was performed in Stata (http://www.stata.com) to determine any association between cross-sectional trends in cognitive ability and allele frequency. Test scores were normally distributed. Data were adjusted for age, gender, hypertension and diabetes. No correction was made for multiple testing, as this was an attempt to replicate previous findings, and the majority of cognitive tests were moderately/highly correlated (Table 1). Novel data investigating epistatic interactions were also uncorrected and should be treated as exploratory. Power calculations were estimated in Stata (2001).
Table 1. Correlation values of cognitive tests
|AH1||1.00|| || || || || || || || || || |
|AH2||0.75||1.00|| || || || || || || || || |
|ACT||0.62||0.58||1.00|| || || || || || || || |
|RL||0.45||0.49||0.54||1.00|| || || || || || || |
|MHA||0.61||0.43||0.29||0.23||1.00|| || || || || || |
|MHB||0.59||0.42||0.32||0.22||0.78||1.00|| || || || || |
|IR||0.31||0.23||0.28||0.21||0.18||0.26||1.00|| || || || |
|DR||0.32||0.28||0.34||0.27||0.25||0.31||0.64||1.00|| || || |
|CR||0.45||0.34||0.43||0.31||0.39||0.42||0.49||0.56||1.00|| || |
HLA-DRB1 polymorphisms were analysed according to which broad antigen group they belonged to (HLA-DR1-7) (new nomenclature listed in brackets). These comprise DR1 (all 01 alleles), DR2 (all 15 and 16 alleles), DR3 (*0301), DR4 (all 04 alleles), DR5 (all 11 and 12 alleles), DR6 (all 13 and 14 alleles) and DR7 (*0701). Analysis was performed for the presence or absence of the DR1-7. DR8-10 was not investigated due to low frequency. The CTSD polymorphism was analysed for the presence or absence of the T allele. This approach was used, because only two volunteers were homozygous mutant. Analysis of the APOE polymorphism was performed by comparing APOEɛ4-positive volunteers against APOEɛ4-negative volunteers. Individuals who possessed both the ɛ2 and ɛ4 allele were excluded from analysis due to the possible protective effect of ɛ2.
Polymorphisms were also analysed in combination to investigate possible epistatic interactions between genes. For example, CTSD and APOE interactions were determined by comparing CTSD T(+)/APOEɛ4(–), CTSD T(–)/APOEɛ4(+) and CTSD(+)/APOEɛ4 (+) volunteers against CTSD T(–)/APOEɛ4 (–) volunteers. The same approach was taken when comparing CTSD with HLA-DR and APOE with HLA-DR.
Allele and genotype frequencies were similar to those previously described in Caucasian controls (Table 2). CTSD and APOE allele and genotype frequencies have previously been reported (Payton et al. 2003; Pendleton et al. 2002). All genotypes were in Hardy–Weinberg equilibrium.
Table 2. HLA-DR allele frequencies in cognitive study volunteers and previously reported controls
|HLA-DRB1||% Allele frequency|
|APOE||% Genotype frequency||% Allele frequency|
| ||ɛ2/ɛ2||ɛ2/ɛ3||ɛ2/ɛ4||ɛ3/ɛ3||ɛ3/ɛ4||ɛ4/ɛ4|| ||ɛ2||ɛ3||ɛ4|
|Cognitive (756)||0.3||14.3||2.0||58.9||23.0||1.6|| ||8.0||78.0||14.0|
|Utermann†||0.1||14.0||2.0||59.0||23.0||2.0|| || || || |
|CTSD||% Genotype frequency||% Allele frequency|
| ||CC||CT||TT|| || || || ||C||T|| |
|Cognitive (766)||84.5||15.3||0.3|| || || || ||92.0||8.0|| |
|Papassotiropoulos‡ (191)||86.4||13.6||0.0|| || || || ||93.2||6.8|| |
The CTSD T allele was associated with lower scores in tests of fluid intelligence (AH2, P = 0.010), processing speed [ACT and RL (P = 0.001 and 0.012, respectively)] and spatial memory (P = 0.016) (Table 3). No influence on other memory or vocabulary abilities was observed. HLA-DR1 significantly increased CR ability (P = 0.006) but had no significant influence on any other cognitive tests. Conversely, HLA-DR5 was associated with a decrease in all memory abilities. This reached significance for delayed recall (P = 0.014) and spatial memory (P = 0.003) and neared significance for SEM (P = 0.054). HLA-DR5 had no influence on any other cognitive abilities. No association was observed between cognitive tests and other HLA-DR polymorphisms. No differences in any cognitive abilities were observed between APOEɛ4-positive and APOEɛ4-negative volunteers.
Table 3. Influence of CTSD, HLA-DRB1 and APOE alleles on cognitive abilities
Analysis of genes in combination found that CTSD T/APOEɛ4-positive volunteers scored lower on tests of fluid intelligence, processing speed and several memory tests when compared against CTSD T/APOEɛ4-negative volunteers (Table 4). This reached significance for fluid intelligence (AH1 P = 0.015), processing speed (ACT P = 0.001; RL P = 0.013) and the immediate recall tests (P = 0.029). Scores were lower in the CTSD T/APOEɛ4-positive volunteers than when either polymorphism was analysed independently. Finally, CTSD T/HLA-DR2-positive volunteers scored significantly lower on the ACT (P = 0.005), RL (P = 0.014), CL (P = 0.003) and spatial tests (P = 0.001) compared against CTSD T/DR2-negative volunteers (Table 5). No other interactions were observed between CTSD and HLA-DR or between HLA-DR and APOE.
Table 4. Interactions between APOE and CTSD alleles
Table 5. Interactions between HLA-DR2 and CTSD alleles
Our results show that the CTSD polymorphism not only influences fluid intelligence but is also associated with the regulation of processing speed and spatial memory in an elderly population. We have also shown that on its own APOEɛ4 has no effect on any cognitive domain in a non-demented population. However, the presence of the CTSD T allele and APOEɛ4 together reduced fluid intelligence, processing speed and several memory abilities more than when the CTSD T allele and APOEɛ4 were analysed independently. Although, the numbers of volunteers carrying both these alleles were small (n = 31) interactions between these two polymorphisms have previously been reported in AD (Menzer et al. 2001; Ntais et al. 2004; Papassotiropoulos et al. 2000). In addition, a biological interaction between these two genes is likely, given that CTSD is involved in several AD-related processes, including APP processing, and APOEɛ4 may be associated with an increased deposition of β-amyloid, oxidative stress, neuroinflammation and lipid dysfunction in AD brains (Refolo & Fillit 2004). The precise mechanism of how CTSD and APOE influence cognitive ability in non-demented individuals is unclear. Although it is possible that some of our volunteers are beginning to show early signs of dementia, at the time of testing, they scored maximally on the Mini Mental Examination, and at the time of venesection, which was over 10 years later, they still showed no signs of dementia. As this is an ongoing study, the role of these genes in demented and non-demented individuals will be determined eventually.
Our results suggest that HLA-DR status may also have a role in regulating memory performance. When analysed independently, HLA-DR5 reduced all memory abilities but had the largest influence on DR and SR. In contrast, HLA-DR1 was only seen to significantly enhance CR, although tests of DR and IR, which are moderately correlated with CR, were also enhanced although not significantly. In a previous study published earlier this year, it was reported that DR1 enhanced scores in the Controlled Word Association Test (expressive language integrity), and conversely DR5 reduced scores in the Boston naming test (measure of executive function) (Shepherd et al. 2004). The use of different testing methods means that direct comparisons with our results cannot be made. However, we found no association between DR5 and tests of fluid intelligence that will have an executive component. Conflicting results may also be caused by insufficient power. The original study utilized 151 unselected individuals. In contrast, our sample size of over 766 individuals provided over 95% power at P < 0.05 to detect the association between CTSD and the CTSD/APOE interaction and processing speed (ACT). We also observed an interaction between CTSD and HLA-DR2. All tests of memory and processing speed, with the exception of SEM, were lower in CTSD T/HLA-DR2-positive volunteers than when these alleles were analysed independently. This reached significance for both tests of processing speed, CR and SR. Interestingly, it has been shown that DR15 (DR2), which is also strongly associated with MS, binds with greater affinity to MBP and prevents its cleavage by CTSD (Vergelli et al. 1997). Despite having 80% power to detect the association between the CTSD/HLA-DR2 interaction and the ACT, the result should be treated with caution given both these alleles were present in only 29 volunteers. HLA has been implicated in atherosclerosis, MS and AD, all of which can influence cognitive functioning (Fraser & Stark 2003; Gonzalez-Gay et al. 2004; 't Hart et al. 2001; Neill et al. 1999). Given that we have no direct measures of inflammation, brain disease or vascular disease, the precise mechanism that HLA uses to determine cognitive abilities in non-demented individuals is unknown.
An additional finding of this study was that CTSD, when analysed independently, influenced fluid intelligence and processing speed but not memory abilities, while HLA influenced memory abilities but not processing speed or fluid intelligence. This suggests that HLA influences memory regions such as the hippocampus, parahippocampus and perirhinal cortex and CTSD influences prefrontal cortex and more global regions involved in processing speed. Domain-specific effects are not uncommon in cognitive genetics. For example, polymorphisms in the brain-derived neurotrophic factor and catechol-O-methyltransferase genes have been specifically associated with episodic memory and executive function, respectively (Egan et al. 2001; Egan et al. 2003; Joober et al. 2002; Malhotra et al. 2002; Rybakowski et al. 2003). Alternatively, less-convincing results such as the HLA-DR1 association may be explained by type I error.
While age-related cognitive impairment is well-documented (reviewed by Rabbitt & Lowe 2000), the underlying mechanisms are poorly understood. A number of theories have been proposed that may influence cognition in the elderly including the inflammatory hypothesis of ageing (Chung et al. 2002) and the mitochondrial-lysosomal hypothesis of ageing (Brunk & Terman 2002). Our results suggest that components from both these mechanisms may have a role in regulating cognitive ability. A number of reports have implicated inflammatory mechanisms as a cause of cognitive dysfunction in both non-demented (Schmidt et al. 2002; Weaver et al. 2002; Yaffe et al. 2003) and demented (Ho et al. 2005) individuals. The putative protective role of anti-inflammatory treatment in demented and non-demented individuals also suggests a role for inflammation and its regulation as a cause of cognitive dysfunction (Rogers et al. 1993; McGeer et al. 1996). The mitochondrial-lysosomal hypothesis of ageing proposes that within postmitotic cells, such as neurones, there is an increase in the production of free radicals by aged mitochondria that contributes towards the accumulation of the insoluble protein, lipofuscin (Brunk & Terman 2002). This occurs primarily within the lysosomes and may occupy up to 75% of cell volume. It is believed that lipofuscin-loaded lysosomes act as sinks for lysosomal enzymes, such as CTSD, thus diverting enzyme away from functional lipofuscin-free lysosomes. Consequently, this may affect the processing of proteins prior to antigen presentation to the immune system. While, a large number of inflammatory conditions have been extensively associated with HLA, the role of lysosomal enzymes has been overlooked.
Our results suggest that both the lysosomal enzyme CTSD and HLA-DR regulate cognitive abilities in the non-demented elderly. We have also shown a possible interaction between CTSD and both HLA-DR and APOE. Further investigations of additional HLA loci as well as inflammatory mediators such as tumour necrosis factor α and interleukin-1 and interleukin-6 should also be considered for future research. With an increasing prevalence of age-related cognitive decline, the field of cognitive genetics has enormous potential for identifying susceptibility genes allowing the development of preventative treatments.
This work was supported by the Wellcome Trust.
Blood collection and DNA extraction was partly funded by Research into Ageing.