Dement Geriatr Cogn Disord 2014;38:245–253 DOI: 10.1159/000359964 Accepted: January 20, 2014 Published online: June 25, 2014
© 2014 S. Karger AG, Basel 1420–8008/14/0384–0245$39.50/0 www.karger.com/dem
Original Research Article
Is HCRTR2 a Genetic Risk Factor for Alzheimer’s Disease? Salvatore Gallone a Silvia Boschi a Elisa Rubino a Paola De Martino a Elio Scarpini c Daniela Galimberti c Chiara Fenoglio c Pier Luigi Acutis b Maria Grazia Maniaci b Lorenzo Pinessi a Innocenzo Rainero a a Neurology
II, Department of Neuroscience, University of Turin, and b Istituto Zooprofilattico Piemonte, Liguria e Valle d’Aosta, Turin, and c Neurology Unit, Department of Phatophysiology and Transplantation, University of Milan, Fondazione Cà Granda, IRCCS Ospedale Policlinico, Milan, Italy
Key Words Alzheimer’s disease · Sleep disorders · Hypocretin/orexin system · Polymorphisms · Molecular model Abstract Backgrounds/Aims: Alzheimer’s disease (AD) is one of the main types of dementia affecting about 50–55% of all demented patients. Sleep disturbances in AD patients are associated with the severity of dementia and are often the primary reason for institutionalization. These sleep problems partly resemble the core symptoms of narcolepsy, a sleep disorder caused by a general loss of the neurotransmitter hypocretin. The aim of our study was to investigate whether genetic variants in the hypocretin (HCRT) and in the hypocretin receptors 1 and 2 (HCRTR1, HCRTR2) genes could modify the occurrence and the clinical features of AD and to examine if these possible variants influence the role of the protein in sleep regulation. Methods: Using a case-control strategy, we genotyped 388 AD patients and 272 controls for 10 SNPs in the HCRT, HCRTR1 and HCRTR2 genes. In order to evaluate which residues belong to the HCRTR2 binding site, we built a molecular model. Results: The genotypic and allelic frequencies of the rs2653349 polymorphism were different (χ2 = 5.77, p = 0.016; χ2 = 6.728, p = 0.035) between AD patients and controls. The carriage of the G allele was associated with an increased AD risk (OR 2.53; 95% CI 1.10–5.80). No significant differences were found in the distribution of either genotypic or allelic frequencies between cases and controls in the HCRTR1 polymorphisms rs2271933, rs10914456 and rs4949449 and in the HCRTR2 polymorphism rs3122156. Conclusion: Our data support the hypothesis that the HCRTR2 gene is likely to be a risk factor for AD. The increased risk inferred is quite small, but in the context of a multi-factorial disease, the presence of this polymorphism may significantly contribute to influencing the susceptibility for AD by interacting with other unknown genetic or environmental factors in sleep regulation. © 2014 S. Karger AG, Basel Salvatore Gallone Neurology II, Department of Neuroscience University of Turin Via Cherasco No. 15, IT–10126 Turin (Italy) E-Mail salvatore.gallone @ unito.it
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© 2014 S. Karger AG, Basel www.karger.com/dem
Gallone et al.: Is HCRTR2 a Genetic Risk Factor for Alzheimer’s Disease?
Introduction
Alzheimer’s disease (AD) is the most prevalent form of dementia and represents an increasing problem in modern society. The disease has a complex aetiology involving the interplay of both genetic and environmental factors [1]. A number of genetic risk factors for AD have been suggested [2–5]; however, only the apolipoprotein E (APOE) ε4 allele, which lowers the age of onset and accelerates the cognitive decline, has a large effect [6, 7]. AD is a neurodegenerative disorder that affects multiple brain areas as well as types of neurons and most likely includes the primary sleep-regulating systems. As the hypocretin system is affected in various neurodegenerative diseases such as Parkinson’s and Huntington’s disease [8–10], we hypothesized that the neurodegenerative process in AD might also affect the hypocretin system, which could contribute to the sleep disturbances of AD patients. The observation of Friedman et al. [11], who have shown an inverse relation between lumbar CSF hypocretin-1 concentration and the amount of daytime naps of AD patients, supports this possibility. In the literature, it has been reported that both the neurotransmitter system and the hypocretin/orexin system are involved in neurological diseases [12, 13]. The hypocretin system, consisting of the peptides hypocretin-1 and hypocretin-2, also called orexin-A and orexin-B, and the G-protein-coupled HCRT receptors (HCRTR1 and HCRTR2), is distributed in the lateral hypothalamus, gastrointestinal tract and endocrine organs [14]. The hypocretin receptors are highly conserved across mammalian species, and the human HCRTR1 and HCRTR2 genes show an overall sequence identity of 64%, with weak conservation of the extracellular N-terminal domain of the intracellular loop III and the C-terminal tail. HCRTR1 exhibits a moderately higher affinity for hypocretin-1 than for hypocretin-2, whereas HCRTR2 has an approximately equal affinity for hypocretin-1 and hypocretin-2 [15]. Consistent with the widespread projections, the two hypocretin receptors are also distributed throughout the central nervous system (CNS) [16, 17], but their differential distributions indicate distinct roles for each receptor in the functions of the neuropeptide. In the literature, it is reported that the 1246G→A polymorphism of the HCRTR2 gene is not associated with migraine [18]; however, the same polymorphism is related to cluster headache [19]. No association studies between HCRTR polymorphisms and AD have been performed so far. Methods Patients and Controls A total of 388 consecutive unrelated AD patients (127 males, 261 females; mean age ± SD 75.94 ± 8.59 years) attending the Neurology II, Department of Neuroscience, University of Turin, and the Department of Neurological Sciences, ‘Dino Ferrari’ Centre, University of Milan, were involved in this case-control association study. All patients underwent a standard battery of examinations, physical and neurological examination, screening laboratory tests, neurocognitive evaluation and neuroimaging. Cognitive dysfunctions were assessed by the Mini-Mental State Examination (MMSE) [20]. The diagnosis of AD was made according to the NINCDS-ADRDA criteria [21]. A group of 272 healthy subjects (90 males, 182 females, mean age 72.09 ± 7.06 years; mean age at sampling 71.18 ± 6.76 years) was used as controls. They were healthy blood donors and were screened by a neurologist in order to exclude neurological disorders. Written informed consent was obtained from all participants, and the study was approved by the Hospital Ethics Committee. DNA Isolation Genomic DNA was extracted using the QIAamp_Mini Kit (Qiagen S.p.A., Italy) from 200 μl of peripheral blood. DNA samples were aliquoted and stored at –20 ° C until use.
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Dement Geriatr Cogn Disord 2014;38:245–253 DOI: 10.1159/000359964
© 2014 S. Karger AG, Basel www.karger.com/dem
Gallone et al.: Is HCRTR2 a Genetic Risk Factor for Alzheimer’s Disease?
SNP Genotyping We genotyped cases and controls for 5 polymorphisms (rs760282, rs9902709, rs4796777, rs8072081 and rs8072099) of the HCRT gene, 3 polymorphisms (rs2271933, rs10914456 and rs4949449) of the HCRTR1 gene and 2 polymorphisms (rs2653349 and rs3122156) of the HCRTR2 gene selected from the SNP database of the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov/). All polymorphisms were analysed by enzymatic digestion. PCR reactions were performed in a final volume of 25 μl, with 90 ng of genomic DNA, 0.2 units of Taq Gold DNA polymerase, 250 nM of each primer, 1.5 mM of MgCl2 and 50 mM of dNTPs. PCR conditions were performed with initial denaturation at 95 ° C for 10 min, 35 cycles at 95 ° C for 1 min at specific temperature for each primer, 72 ° C for 1 min and a final elongation at 72 ° C for 5 min. PCR products were electrophoresed on a 2% agarose 1× TBE gel and stained with ethidium bromide. ApoE Genotyping The tri-allelic (ε2-ε3-ε4) polymorphism of APOE was assessed with a single-stage PCR-based method and the digestion with the restriction enzyme HhaI (Fermentas) as previously described [22]. Molecular Model We conducted a research with HCRTR2, which was the only polymorphism with a statistical difference in the distribution of genotype frequencies (GF) and allele frequencies (AF) between cases and controls (http://www.rcsb.org/pdb/results; pdb code 1wso). The molecular description of this result reported that the length of this structure has only 34 residues. For this reason, in order to build a better molecular model of HCRTR2, the crystal structure of bovine rhodopsin was selected. The alignment between the sequence of the orexin receptor 2 (OX2R) and the sequence of bovine rhodopsin was built based on the fingerprints available at http://www.bioinf.manchester.ac.uk/dbbrowser. Since the sequence of OX2R was not present in the alignment retrieved, a particular fingerprint containing all sequences for the peptide family and the human OPSD sequence (human homologue of the bovine rhodopsin) was extracted from the global G-protein-coupled receptor (GPCR) fingerprint in order to increase the precision of the alignment. The sequence of OX2R was aligned with this alignment using the program ClustalW. Once the alignment between the human sequences of OX2R and OPSD had been obtained, the final alignment was derived substituting the human OPSD sequence with the bovine one. The transmembrane regions were selected based on the secondary structure of the crystal structure of bovine rhodopsin (pdb code 1f88), and 3 transmembrane predictions were made on the HCRTR2 sequence obtained by means of the TMAP programs [23]. To evaluate which residues belong to the HCRTR2 binding site, the program PASS was used [24]. In order to identify the residues surrounding the binding pockets found with PASS, all spheres within a certain radius from the centre of the binding pocket were grouped. Moreover, each binding site was classified as inner, outer or partly inner and partly outer based on the distance from the molecular surface of the residues participating in it. The different binding sites obtained are given in table 1. Docking experiments were performed in order to evaluate which of these binding sites actually binds hypocretin. The NMR structure of hypocretin-2 in water (pdb code 1CQ0) is available for downloading at the Protein Data Bank (PDB) site. Starting from the NMR structure obtained in water, different conformations were derived, which were then used for the docking experiments. Hypocretin-2 residues contacting HCRTR2 were analysed using the program YASARA. Subsequently, each residue at the interface was assigned to the binding pocket previously identified. In order to evaluate if residue 308 might be part of the dimerization interface either in a homodimer or a heterodimer with the orexin receptor 1 (OX1R), a correlated mutation analysis was performed on sequences belonging to the orexin and neuropeptide FF, QRFP class A GPCR subfamily. The correlated mutation analysis technique allows for the identification of highly correlated patterns of differentiation between aligned sequences of proteins. Table 2 shows the basic principle. Because of sequencing errors and species divergence, the actual configurations of the real sequences might be different from the ideal configurations described in the table. Statistics Hardy-Weinberg equilibrium was verified for all populations tested. Statistical analyses were performed using SigmaStat version 1.0. The χ2 test was used to compare AF and GF between cases and controls. ANOVA – followed by Bonferroni correction for multiple comparisons – was performed to compare the patients’ clinical characteristics according to their genotypes. The odds ratio (OR) was calculated with its 95% confidence interval (CI). The level of statistical significance was taken at p < 0.05.
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Table 1. Different binding sites found by PASS
Binding Residues site 1
2
3
4
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Volume of the Classifipocket, Å3 cation
127-CYS 130-ILE 131-PRO 134-GLN 135-THR 138-VAL 142-VAL 145-LEU 146-SER 218-ILE 220-PRO 223-TYR 224-HIS 227-PHE 228-PHE 232-TYR 235-PRO 236-LEU 39-MET 310-LEU 313-PHE 314-ALA 317-TYR 318-LEU 320-ILE 321-SER 322-ILE 323-LEU 324-ASN 325-VAL 350-HIS 64-VAL 67-VAL 96-LEU 137-SER 138-VAL 141-SER 144-THR 145-LEU 148-ILE 305-MET 308-VAL 309-VAL 312-VAL 313-PHE 315-ILE 316-CYS 352-LEU 353-VAL 355-ALA 356-ASN 357-SER 358-ALA 359-ALA 360-ASN 362-ILE 363-ILE 143-LEU 147-CYS 150-LEU 151-ASP 154-TYR 168-ARG 171-ASN 172-SER 175-ILE 178-ILE 179-VAL 182-ILE 226-CYS 229-LEU 230-VAL 234-ALA 238-LEU 53-TYR 54-GLU 57-LEU 58-ILE 61-TYR 110-ALA 111-THR 113-VAL 114-VAL 115-ASP 116-ILE 130-ILE 343-TYR 346-PHE 347-THR 350-HIS 351-TRP 153-TRP 239-MET 243-TYR 246-ILE 247-PHE 299-ARG 300-ARG 303-ALA 304-ARG 307-MET 308-VAL 310-LEU 311-LEU 314-ALA 98-LEU 99-ALA 102-LEU 132-TYR 136-VAL 140-VAL 176-ILE 177-TRP 180-SER 181-CYS 184-MET 185-ILE 188-ALA 91-TYR 92-PHE 95-ASN 144-THR 147-CYS 148-ILE 151-ASP 152-ARG 168-ARG 169-ALA 172-SER 173-ILE 176-ILE 64-VAL 65-PHE 68-ALA 100-ASP 103-VAL 104-THR 107-CYS 137-SER 354-TYR 357-SER 44-THR 47-PRO 48-ALA 56-LYS 57-VAL 60-TYR 61-LEU 103-GLN 104-ALA 58-ILE 61-TYR 62-ILE 65-PHE 66-VAL 69-LEU 112-LEU 115-ASP 116-ILE 75-VAL 76-CYS 78-ALA 93-ILE 94-VAL 97-SER 98-LEU 364-TYR 91-TYR 94-VAL 95-ASN 98-LEU 170-ARG 173-ILE 174-VAL 177-TRP 298-ALA 301-LYS 302-THR 304-ARG 305-MET 364-TYR 318-LEU 319-PRO 322-ILE 344-ALA 345-TRP 348-PHE 150-LEU 153-TRP 154-TYR 241-LEU 242-ALA 245-GLN 69-LEU 73-VAL 101-VAL 104-THR 105-ILE 108-LEU 323-LEU 326-LEU 343-TYR 345-TRP 346-PHE 344-ALA 347-THR 348-PHE 351-TRP 352-LEU 185-ILE 186-PRO 189-ILE 219-TYR 222-MET
Table 2. The basic principle of the correlated mutation analysis technique
Position
N1 N2 N3 N4 N5
2,097.95
inner/outer
1,258.32
outer
1,077.36
inner/outer
1,099.08
outer
896.41
inner/outer
737.16
inner/outer
534.49
outer
317.35 462.11
outer
454.87
outer
425.92 476.59
outer outer
302.87 346.30 281.16 158.11 194.30 194.30 230.49
outer outer outer inner/outer outer outer outer
Sequence α1
α1
α2
β1
β2
β3
β4
W L F L Q
W V F L Q
W A F L Q
W I N F S
W L N F S
W V N F N
W I N F N
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Results
Table 3 shows the GF and AF of the 5 polymorphisms examined in the HCRTR1 (rs2271933, rs10914456 and rs4949449) and HCRTR2 genes (rs2653349 and rs3122156) as well as the comparison between healthy controls and AD patients. We also examined 5 SNPs (rs760282, rs9902709, rs4796777, rs8072081 and rs8072099) in the HCRT gene; however, unfortunately, none of these SNPs were informative for the two study populations. Hardy-Weinberg equilibrium was verified for both populations, and everything was in equilibrium. No significant differences were found in the distribution of either genotypic or allelic frequencies between cases and controls in the HCRTR1 polymorphisms rs2271933, rs10914456 and rs4949449 and in the HCRTR2 polymorphism rs3122156. Conversely, analysing the rs2653349G>A (1246G>A) polymorphism corresponding to the substitution Val308Ile, a statistical difference was found in the distribution of GF and AF between cases and controls. The AF for allele G was 0.74% in controls and 0.81% in AD patients, and the AF for allele A was 0.26% in controls and 0.19% in AD patients (χ2 = 6.728, p = 0.035). A significant difference in the GF between cases and controls was found (χ2 = 5.770, p = 0.016). Subsequently, we analysed the recessive (AA vs. GA+GG) and dominant (AA+GA vs. GG) models for allele G. The comparison between AA and GA+GG revealed a difference between cases and controls (χ2 = 5.172, p = 0.023), with an increased risk of AD in GA+GG carriers compared to AA carriers (OR 2.53; 95% CI 1.10–5.80) according to a recessive model. When we divided the AD patients into two different subgroups (males and females), there was no statistically significant difference. The main clinical and neuropsychological characteristics of the AD patients are shown in table 4. Different genotypes had no significant effect on the examined clinical characteristics of the disease. Our molecular model revealed that residues on the surface of the biggest cavities involving inner and outer amino acids are very likely participating in the HCRTR2 binding site. We found that the changes at position 11 (L-leucine to L-alanine) and at positions 14 and 15 (L-leucine to D-leucine) located in the first helix selectively reduce the potency for HCRT1 without altering the selectivity for HCRT2. This indicates that residues 11, 14 and 15 are very likely involved in receptor recognition. Of all different complexes returned by the docking programmes, the complexes in which residues 11, 14 and 15 and the C-terminal part of orexin-B contact HCRT2 were selected for analysis. Residue 308 is not part of the orexin-B binding pocket, although it is on the surface of a binding pocket. The residues at positions N1–N5 for 7 different hypothetical α- and β-receptors (which may be further divided into subtypes 1 and 2) are not necessarily sequential. The W residue at position N1 is conserved. This indicates that mutations at N1 are likely to result in a loss of function. The same might be said for the residues at position N3. However, since a mutation of this Phe to Asn is correlated with a corresponding mutation from Leu to Phe at position N4, the residues at positions N3 and N4 are said to be correlated, and the second mutation might produce the regain of the function lost by the first mutation. The variability at position N2 indicates that any hydrophobic residue might be present there, whereas position N5 is related with the subtype (e.g. differentiating between β1- and β2-receptors). Discussion
To the best of our knowledge, this is the first study to examine the association between hypocretin receptor genes and AD. Additional studies in different populations are warranted in order to confirm our data. Genetic association studies are considered particularly useful in deciphering the genetic basis of complex diseases such as AD.
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Table 3. GF and AF of polymorphisms in AD patients and controls
rs2271933 G>A AD patients Male Female Total Controls Male Female Total
G/G
G/A
A/A
G, % A, %
50 (39.37) 60 (47.24) 17 (13.39) 0.63 0.37 105 (40.23) 121 (46.36) 35 (13.41) 0.63 0.37 155 (39.95) 181 (46.65) 52 (13.40) 0.63 0.37 30 (33.33) 43 (47.77) 17 (18.90) 0.57 0.43 63 (34.61) 89 (48.90) 30 (16.49) 0.59 0.41 93 (34.19) 132 (48.52) 47 (17.29) 0.58 0.42
rs10914456 C>T C/C T/C T/T C, % AD patients Male 42 (33.07) 67 (52.76) 18 (14.17) 0.6 Female 105 (40.23) 108 (41.38) 48 (18.39) 0.61 Total 147 (37.89) 175 (45.10) 66 (17.01) 0.61 Controls Male 31 (34.44) 40 (44.44) 19 (21.12) 0.56 Female 63 (34.61) 80 (43.96) 39 (21.43) 0.56 Total 94 (34.56) 120 (44.11) 58 (21.33) 0.57 rs4949449 G>T AD patients Male Female Total Controls Male Female Total rs2653349 G>A AD patients Male Female Total Controls Male Female Total rs3122156 T>G AD patients Male Female Total Controls Male Female Total
G/G
G/T
T/T
T, % 0.4 0.39 0.39 0.44 0.44 0.43
G, % T, %
43 (33.86) 64 (50.40) 20 (15.74) 0.59 0.41 92 (35.25) 134 (51.34) 35 (13.41) 0.6 0.4 135 (37.80) 198 (51.03) 55 (14.17) 0.63 0.37 30 (33.33) 44 (48.88) 16 (17.79) 0.57 0.43 58 (31.86) 88 (48.35) 36 (19.79) 0.56 0.44 88 (32.35) 132 (48.53) 52 (19.12) 0.56 0.44 G/G
G/A
A/A
G, % A, %
81 (63.78) 43 (33.86) 3 (2.36) 176 (67.43) 75 (28.73) 10 (3.84) 257 (66.24)a 118 (30.41)a 13 (3.35)
0.81 0.19 0.82 0.18 0.81b 0.19
52 (57.77) 104 (57.14) 156 (57.53)
0.75 0.25 0.74 0.26 0.74 0.26
T/T
31 (34.44) 7 (7.79) 63 (34.61) 15 (8.25) 94 (34.56) 22 (8.09) G/T
G/G
65 (51.18) 50 (39.37) 12 (9.45) 140 (53.64) 101 (38.7) 20 (7.66) 205 (52.84) 151 (38.92) 32 (8.24)
T, % G, % 0.71 0.29 0.73 0.27 0.73 0.27
48 (53.33) 33 (36.66) 9 (10.01) 0.72 0.28 98 (53.84) 67 (36.81) 17 (9.35) 0.72 0.28 146 (53.68) 100 (36.76) 26 (9.56) 0.73 0.27
Values are the number (%) of patients positive for each genotype. p values were calculated by the χ2 test from 3 × 2 (genotype) or 2 × 2 (allele) contingency tables. a GF χ2 = 5.77, p = 0.016; b AF χ2 = 6.72, p = 0.035.
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Table 4. Effects of the different polymorphisms on clinical features in patients with AD
rs2271933 G>A GG (n = 155) GA (n = 181) AA (n = 52) p (ANOVA) rs10914456 C>T CC (n = 147) CT (n = 175) TT (n = 66) p (ANOVA) rs4949449 G>T GG (n = 135) GT (n = 198) TT (n = 55) p (ANOVA) rs2653349 G>A GG (n = 257) GA (n = 118) AA (n = 13) p (ANOVA) rs3122156 T>G TT (n = 205) GT (n = 151) GG (n = 32) p (ANOVA) ApoE E2E2 (n = 0) E2E3 (n = 14) E3E3 (n = 125) E3E4 (n = 87) E4E4 (n = 12) p (ANOVA)
Age at sampling
Age of onset
MMSE score
76.16 ± 8.31 75.89 ± 8.20 76.00 ± 8.00 0.96
73.68 ± 7.93 73.23 ± 7.87 72.75 ± 8.36 0.85
19.19 ± 5.63 19.08 ± 5.22 19.20 ± 6.27 0.99
76.34 ± 8.122 75.53 ± 8.52 76.56 ± 7.54 0.64
73.60 ± 8.04 73.08 ± 7.97 73.58 ± 7.61 0.89
18.94 ± 5.84 19.17 ± 5.26 19.80 ± 5.50 0.74
76.14 ± 8.19 75.81 ± 8.37 76.48 ± 7.89 0.88
74.62 ± 7.30 72.67 ± 7.99 71.81 ± 9.20 0.13
18.51 ± 5.72 19.45 ± 5.23 19.19 ± 6.22 0.54
75.81 ± 8.90 76.83 ± 6.72 78.80 ± 4.39 0.46
72.94 ± 8.49 74.20 ± 6.91 73.63 ± 5.60 0.55
18.95 ± 5.63 19.38 ± 5.30 19.86 ± 5.95 0.82
75.80 ± 8.16 76.24 ± 8.45 76.22 ± 7.59 0.89
72.73 ± 8.07 73.74 ± 8.01 75.63 ± 5.84 0.33
18.61 ± 5.69 20.09 ± 5.11 17.56 ± 5.41 0.08
79.75 ± 3.57 76.40 ± 8.45 76.03 ± 7.04 73.17 ± 6.22 0.21
77.09 ± 4.41 74.40 ± 8.69 73.26 ± 7.18 68.20 ± 5.28 0.052
19.45 ± 5.08 19.63 ± 5.22 19.87 ± 5.37 21.75 ± 4.33 0.74
The results of our study show that the V308I polymorphism of the HCRTR2 gene is significantly associated with AD. Both allelic and genotypic frequencies of the HCRTR1 and HCRTR2 genes were similarly distributed between cases and controls. AF and GF in this study are in agreement with published data on the HapMap site (www.hapmap.ncbi.nlm.nih.gov) with regard to the distribution of the European population. Our results are supported by two different genome-wide association studies published on AD at GWAS Central (https://www.gwascentral.org/generegion/phenotypes). These studies (HGVPM72 and HGVPM576) reported a p value threshold –log p ≥ 3 in the 6p12.1 region in which the HCRT2 gene is located. The mechanism by which this SNP determines an increased risk is still unknown. It should, however, be taken into account that this polymorphism leads to an amino acidic change and, therefore, theoretically, the function of the protein could be affected. Data of the correlated mutation analysis and the participation of residue 308 in a binding pocket indicate that residue 308 might be at the dimer interface and that the Val308Ile polymorphism could influence the dimerization process of the protein. It might be argued that only the conserved amino acids are important for the basic function of the protein and that mutations of one of the amino acids may result in a loss of function. However, many of the
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amino acids that are correlated within a family are conserved in a subfamily, indicating that residues involved in correlated mutations may also have a similar role. From the analysis of the behaviour of mutated receptors belonging to other GPCR subfamilies, it appears that the basic function of the receptor involves the conserved residues, while the finer details of specificity involve the correlated residues. Genetic association studies are exposed to several biases (the systematic distortion of a statistic) such as phenotypic definition, adequate sample size of cases and controls and population stratification. The growing knowledge concerning the role of hypocretins/orexins in different neurological conditions has generated considerable interest in developing smallmolecule hypocretin receptor antagonists as a novel therapeutic strategy. Hypocretin antagonists, especially those that block Hcrtr1 or both Hcrtr1 and Hcrtr2 receptors, have been studied mainly as new drugs for sleep disorders. In experimental animal models, hypocretin/ orexin antagonists (almorexant, suvorexant) clearly promote sleep, and clinical results are encouraging [25–28]. However, the exact relationship between a partial loss of hypocretin and the occurrence of clinical symptoms remains unknown. In a rodent study, microinjections of prepro-hypocretin short interfering ribonucleic acids resulting in a 60% decrease in hypocretin messenger ribonucleic acid led to REM sleep alterations [29]. Another rodent study showed that lesioning 70% of hypocretin neurons results in both a decreased CSF hypocretin concentration and REM sleep disturbances [30]. This means that a partial loss of hypocretin functioning may lead to sleep disturbances, at least in rodents. In conclusion, according to these findings, the HCRTR2 1246G>A SNP is likely to be a risk factor for AD. The increased risk inferred is quite small, but in the context of a multi-factorial disease, the presence of this polymorphism may significantly contribute to influencing the susceptibility for AD by interacting with other unknown genetic or environmental factors. Nevertheless, further studies in larger populations are needed to draw definitive conclusions, together with the neuropathological confirmation of clinical diagnoses, and probably future studies should focus on the direct relationship between loss of hypocretin neurotransmission and clinical symptoms. Acknowledgments This work was supported by 2008 grants from the Regione, Ministero dell’Istruzione, dell’Università e della Ricerca Scientifica (MIUR) of Italy, the Italian Ministry of Health (Ricerca Corrente) and the Fondazione Monzino.
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Original Research Article
Is HCRTR2 a Genetic Risk Factor for Alzheimer’s Disease? Salvatore Gallone a Silvia Boschi a Elisa Rubino a Paola De Martino a Elio Scarpini c Daniela Galimberti c Chiara Fenoglio c Pier Luigi Acutis b Maria Grazia Maniaci b Lorenzo Pinessi a Innocenzo Rainero a a Neurology
II, Department of Neuroscience, University of Turin, and b Istituto Zooprofilattico Piemonte, Liguria e Valle d’Aosta, Turin, and c Neurology Unit, Department of Phatophysiology and Transplantation, University of Milan, Fondazione Cà Granda, IRCCS Ospedale Policlinico, Milan, Italy
Key Words Alzheimer’s disease · Sleep disorders · Hypocretin/orexin system · Polymorphisms · Molecular model Abstract Backgrounds/Aims: Alzheimer’s disease (AD) is one of the main types of dementia affecting about 50–55% of all demented patients. Sleep disturbances in AD patients are associated with the severity of dementia and are often the primary reason for institutionalization. These sleep problems partly resemble the core symptoms of narcolepsy, a sleep disorder caused by a general loss of the neurotransmitter hypocretin. The aim of our study was to investigate whether genetic variants in the hypocretin (HCRT) and in the hypocretin receptors 1 and 2 (HCRTR1, HCRTR2) genes could modify the occurrence and the clinical features of AD and to examine if these possible variants influence the role of the protein in sleep regulation. Methods: Using a case-control strategy, we genotyped 388 AD patients and 272 controls for 10 SNPs in the HCRT, HCRTR1 and HCRTR2 genes. In order to evaluate which residues belong to the HCRTR2 binding site, we built a molecular model. Results: The genotypic and allelic frequencies of the rs2653349 polymorphism were different (χ2 = 5.77, p = 0.016; χ2 = 6.728, p = 0.035) between AD patients and controls. The carriage of the G allele was associated with an increased AD risk (OR 2.53; 95% CI 1.10–5.80). No significant differences were found in the distribution of either genotypic or allelic frequencies between cases and controls in the HCRTR1 polymorphisms rs2271933, rs10914456 and rs4949449 and in the HCRTR2 polymorphism rs3122156. Conclusion: Our data support the hypothesis that the HCRTR2 gene is likely to be a risk factor for AD. The increased risk inferred is quite small, but in the context of a multi-factorial disease, the presence of this polymorphism may significantly contribute to influencing the susceptibility for AD by interacting with other unknown genetic or environmental factors in sleep regulation. © 2014 S. Karger AG, Basel Salvatore Gallone Neurology II, Department of Neuroscience University of Turin Via Cherasco No. 15, IT–10126 Turin (Italy) E-Mail salvatore.gallone @ unito.it
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Gallone et al.: Is HCRTR2 a Genetic Risk Factor for Alzheimer’s Disease?
Introduction
Alzheimer’s disease (AD) is the most prevalent form of dementia and represents an increasing problem in modern society. The disease has a complex aetiology involving the interplay of both genetic and environmental factors [1]. A number of genetic risk factors for AD have been suggested [2–5]; however, only the apolipoprotein E (APOE) ε4 allele, which lowers the age of onset and accelerates the cognitive decline, has a large effect [6, 7]. AD is a neurodegenerative disorder that affects multiple brain areas as well as types of neurons and most likely includes the primary sleep-regulating systems. As the hypocretin system is affected in various neurodegenerative diseases such as Parkinson’s and Huntington’s disease [8–10], we hypothesized that the neurodegenerative process in AD might also affect the hypocretin system, which could contribute to the sleep disturbances of AD patients. The observation of Friedman et al. [11], who have shown an inverse relation between lumbar CSF hypocretin-1 concentration and the amount of daytime naps of AD patients, supports this possibility. In the literature, it has been reported that both the neurotransmitter system and the hypocretin/orexin system are involved in neurological diseases [12, 13]. The hypocretin system, consisting of the peptides hypocretin-1 and hypocretin-2, also called orexin-A and orexin-B, and the G-protein-coupled HCRT receptors (HCRTR1 and HCRTR2), is distributed in the lateral hypothalamus, gastrointestinal tract and endocrine organs [14]. The hypocretin receptors are highly conserved across mammalian species, and the human HCRTR1 and HCRTR2 genes show an overall sequence identity of 64%, with weak conservation of the extracellular N-terminal domain of the intracellular loop III and the C-terminal tail. HCRTR1 exhibits a moderately higher affinity for hypocretin-1 than for hypocretin-2, whereas HCRTR2 has an approximately equal affinity for hypocretin-1 and hypocretin-2 [15]. Consistent with the widespread projections, the two hypocretin receptors are also distributed throughout the central nervous system (CNS) [16, 17], but their differential distributions indicate distinct roles for each receptor in the functions of the neuropeptide. In the literature, it is reported that the 1246G→A polymorphism of the HCRTR2 gene is not associated with migraine [18]; however, the same polymorphism is related to cluster headache [19]. No association studies between HCRTR polymorphisms and AD have been performed so far. Methods Patients and Controls A total of 388 consecutive unrelated AD patients (127 males, 261 females; mean age ± SD 75.94 ± 8.59 years) attending the Neurology II, Department of Neuroscience, University of Turin, and the Department of Neurological Sciences, ‘Dino Ferrari’ Centre, University of Milan, were involved in this case-control association study. All patients underwent a standard battery of examinations, physical and neurological examination, screening laboratory tests, neurocognitive evaluation and neuroimaging. Cognitive dysfunctions were assessed by the Mini-Mental State Examination (MMSE) [20]. The diagnosis of AD was made according to the NINCDS-ADRDA criteria [21]. A group of 272 healthy subjects (90 males, 182 females, mean age 72.09 ± 7.06 years; mean age at sampling 71.18 ± 6.76 years) was used as controls. They were healthy blood donors and were screened by a neurologist in order to exclude neurological disorders. Written informed consent was obtained from all participants, and the study was approved by the Hospital Ethics Committee. DNA Isolation Genomic DNA was extracted using the QIAamp_Mini Kit (Qiagen S.p.A., Italy) from 200 μl of peripheral blood. DNA samples were aliquoted and stored at –20 ° C until use.
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Gallone et al.: Is HCRTR2 a Genetic Risk Factor for Alzheimer’s Disease?
SNP Genotyping We genotyped cases and controls for 5 polymorphisms (rs760282, rs9902709, rs4796777, rs8072081 and rs8072099) of the HCRT gene, 3 polymorphisms (rs2271933, rs10914456 and rs4949449) of the HCRTR1 gene and 2 polymorphisms (rs2653349 and rs3122156) of the HCRTR2 gene selected from the SNP database of the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov/). All polymorphisms were analysed by enzymatic digestion. PCR reactions were performed in a final volume of 25 μl, with 90 ng of genomic DNA, 0.2 units of Taq Gold DNA polymerase, 250 nM of each primer, 1.5 mM of MgCl2 and 50 mM of dNTPs. PCR conditions were performed with initial denaturation at 95 ° C for 10 min, 35 cycles at 95 ° C for 1 min at specific temperature for each primer, 72 ° C for 1 min and a final elongation at 72 ° C for 5 min. PCR products were electrophoresed on a 2% agarose 1× TBE gel and stained with ethidium bromide. ApoE Genotyping The tri-allelic (ε2-ε3-ε4) polymorphism of APOE was assessed with a single-stage PCR-based method and the digestion with the restriction enzyme HhaI (Fermentas) as previously described [22]. Molecular Model We conducted a research with HCRTR2, which was the only polymorphism with a statistical difference in the distribution of genotype frequencies (GF) and allele frequencies (AF) between cases and controls (http://www.rcsb.org/pdb/results; pdb code 1wso). The molecular description of this result reported that the length of this structure has only 34 residues. For this reason, in order to build a better molecular model of HCRTR2, the crystal structure of bovine rhodopsin was selected. The alignment between the sequence of the orexin receptor 2 (OX2R) and the sequence of bovine rhodopsin was built based on the fingerprints available at http://www.bioinf.manchester.ac.uk/dbbrowser. Since the sequence of OX2R was not present in the alignment retrieved, a particular fingerprint containing all sequences for the peptide family and the human OPSD sequence (human homologue of the bovine rhodopsin) was extracted from the global G-protein-coupled receptor (GPCR) fingerprint in order to increase the precision of the alignment. The sequence of OX2R was aligned with this alignment using the program ClustalW. Once the alignment between the human sequences of OX2R and OPSD had been obtained, the final alignment was derived substituting the human OPSD sequence with the bovine one. The transmembrane regions were selected based on the secondary structure of the crystal structure of bovine rhodopsin (pdb code 1f88), and 3 transmembrane predictions were made on the HCRTR2 sequence obtained by means of the TMAP programs [23]. To evaluate which residues belong to the HCRTR2 binding site, the program PASS was used [24]. In order to identify the residues surrounding the binding pockets found with PASS, all spheres within a certain radius from the centre of the binding pocket were grouped. Moreover, each binding site was classified as inner, outer or partly inner and partly outer based on the distance from the molecular surface of the residues participating in it. The different binding sites obtained are given in table 1. Docking experiments were performed in order to evaluate which of these binding sites actually binds hypocretin. The NMR structure of hypocretin-2 in water (pdb code 1CQ0) is available for downloading at the Protein Data Bank (PDB) site. Starting from the NMR structure obtained in water, different conformations were derived, which were then used for the docking experiments. Hypocretin-2 residues contacting HCRTR2 were analysed using the program YASARA. Subsequently, each residue at the interface was assigned to the binding pocket previously identified. In order to evaluate if residue 308 might be part of the dimerization interface either in a homodimer or a heterodimer with the orexin receptor 1 (OX1R), a correlated mutation analysis was performed on sequences belonging to the orexin and neuropeptide FF, QRFP class A GPCR subfamily. The correlated mutation analysis technique allows for the identification of highly correlated patterns of differentiation between aligned sequences of proteins. Table 2 shows the basic principle. Because of sequencing errors and species divergence, the actual configurations of the real sequences might be different from the ideal configurations described in the table. Statistics Hardy-Weinberg equilibrium was verified for all populations tested. Statistical analyses were performed using SigmaStat version 1.0. The χ2 test was used to compare AF and GF between cases and controls. ANOVA – followed by Bonferroni correction for multiple comparisons – was performed to compare the patients’ clinical characteristics according to their genotypes. The odds ratio (OR) was calculated with its 95% confidence interval (CI). The level of statistical significance was taken at p < 0.05.
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Table 1. Different binding sites found by PASS
Binding Residues site 1
2
3
4
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Volume of the Classifipocket, Å3 cation
127-CYS 130-ILE 131-PRO 134-GLN 135-THR 138-VAL 142-VAL 145-LEU 146-SER 218-ILE 220-PRO 223-TYR 224-HIS 227-PHE 228-PHE 232-TYR 235-PRO 236-LEU 39-MET 310-LEU 313-PHE 314-ALA 317-TYR 318-LEU 320-ILE 321-SER 322-ILE 323-LEU 324-ASN 325-VAL 350-HIS 64-VAL 67-VAL 96-LEU 137-SER 138-VAL 141-SER 144-THR 145-LEU 148-ILE 305-MET 308-VAL 309-VAL 312-VAL 313-PHE 315-ILE 316-CYS 352-LEU 353-VAL 355-ALA 356-ASN 357-SER 358-ALA 359-ALA 360-ASN 362-ILE 363-ILE 143-LEU 147-CYS 150-LEU 151-ASP 154-TYR 168-ARG 171-ASN 172-SER 175-ILE 178-ILE 179-VAL 182-ILE 226-CYS 229-LEU 230-VAL 234-ALA 238-LEU 53-TYR 54-GLU 57-LEU 58-ILE 61-TYR 110-ALA 111-THR 113-VAL 114-VAL 115-ASP 116-ILE 130-ILE 343-TYR 346-PHE 347-THR 350-HIS 351-TRP 153-TRP 239-MET 243-TYR 246-ILE 247-PHE 299-ARG 300-ARG 303-ALA 304-ARG 307-MET 308-VAL 310-LEU 311-LEU 314-ALA 98-LEU 99-ALA 102-LEU 132-TYR 136-VAL 140-VAL 176-ILE 177-TRP 180-SER 181-CYS 184-MET 185-ILE 188-ALA 91-TYR 92-PHE 95-ASN 144-THR 147-CYS 148-ILE 151-ASP 152-ARG 168-ARG 169-ALA 172-SER 173-ILE 176-ILE 64-VAL 65-PHE 68-ALA 100-ASP 103-VAL 104-THR 107-CYS 137-SER 354-TYR 357-SER 44-THR 47-PRO 48-ALA 56-LYS 57-VAL 60-TYR 61-LEU 103-GLN 104-ALA 58-ILE 61-TYR 62-ILE 65-PHE 66-VAL 69-LEU 112-LEU 115-ASP 116-ILE 75-VAL 76-CYS 78-ALA 93-ILE 94-VAL 97-SER 98-LEU 364-TYR 91-TYR 94-VAL 95-ASN 98-LEU 170-ARG 173-ILE 174-VAL 177-TRP 298-ALA 301-LYS 302-THR 304-ARG 305-MET 364-TYR 318-LEU 319-PRO 322-ILE 344-ALA 345-TRP 348-PHE 150-LEU 153-TRP 154-TYR 241-LEU 242-ALA 245-GLN 69-LEU 73-VAL 101-VAL 104-THR 105-ILE 108-LEU 323-LEU 326-LEU 343-TYR 345-TRP 346-PHE 344-ALA 347-THR 348-PHE 351-TRP 352-LEU 185-ILE 186-PRO 189-ILE 219-TYR 222-MET
Table 2. The basic principle of the correlated mutation analysis technique
Position
N1 N2 N3 N4 N5
2,097.95
inner/outer
1,258.32
outer
1,077.36
inner/outer
1,099.08
outer
896.41
inner/outer
737.16
inner/outer
534.49
outer
317.35 462.11
outer
454.87
outer
425.92 476.59
outer outer
302.87 346.30 281.16 158.11 194.30 194.30 230.49
outer outer outer inner/outer outer outer outer
Sequence α1
α1
α2
β1
β2
β3
β4
W L F L Q
W V F L Q
W A F L Q
W I N F S
W L N F S
W V N F N
W I N F N
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Results
Table 3 shows the GF and AF of the 5 polymorphisms examined in the HCRTR1 (rs2271933, rs10914456 and rs4949449) and HCRTR2 genes (rs2653349 and rs3122156) as well as the comparison between healthy controls and AD patients. We also examined 5 SNPs (rs760282, rs9902709, rs4796777, rs8072081 and rs8072099) in the HCRT gene; however, unfortunately, none of these SNPs were informative for the two study populations. Hardy-Weinberg equilibrium was verified for both populations, and everything was in equilibrium. No significant differences were found in the distribution of either genotypic or allelic frequencies between cases and controls in the HCRTR1 polymorphisms rs2271933, rs10914456 and rs4949449 and in the HCRTR2 polymorphism rs3122156. Conversely, analysing the rs2653349G>A (1246G>A) polymorphism corresponding to the substitution Val308Ile, a statistical difference was found in the distribution of GF and AF between cases and controls. The AF for allele G was 0.74% in controls and 0.81% in AD patients, and the AF for allele A was 0.26% in controls and 0.19% in AD patients (χ2 = 6.728, p = 0.035). A significant difference in the GF between cases and controls was found (χ2 = 5.770, p = 0.016). Subsequently, we analysed the recessive (AA vs. GA+GG) and dominant (AA+GA vs. GG) models for allele G. The comparison between AA and GA+GG revealed a difference between cases and controls (χ2 = 5.172, p = 0.023), with an increased risk of AD in GA+GG carriers compared to AA carriers (OR 2.53; 95% CI 1.10–5.80) according to a recessive model. When we divided the AD patients into two different subgroups (males and females), there was no statistically significant difference. The main clinical and neuropsychological characteristics of the AD patients are shown in table 4. Different genotypes had no significant effect on the examined clinical characteristics of the disease. Our molecular model revealed that residues on the surface of the biggest cavities involving inner and outer amino acids are very likely participating in the HCRTR2 binding site. We found that the changes at position 11 (L-leucine to L-alanine) and at positions 14 and 15 (L-leucine to D-leucine) located in the first helix selectively reduce the potency for HCRT1 without altering the selectivity for HCRT2. This indicates that residues 11, 14 and 15 are very likely involved in receptor recognition. Of all different complexes returned by the docking programmes, the complexes in which residues 11, 14 and 15 and the C-terminal part of orexin-B contact HCRT2 were selected for analysis. Residue 308 is not part of the orexin-B binding pocket, although it is on the surface of a binding pocket. The residues at positions N1–N5 for 7 different hypothetical α- and β-receptors (which may be further divided into subtypes 1 and 2) are not necessarily sequential. The W residue at position N1 is conserved. This indicates that mutations at N1 are likely to result in a loss of function. The same might be said for the residues at position N3. However, since a mutation of this Phe to Asn is correlated with a corresponding mutation from Leu to Phe at position N4, the residues at positions N3 and N4 are said to be correlated, and the second mutation might produce the regain of the function lost by the first mutation. The variability at position N2 indicates that any hydrophobic residue might be present there, whereas position N5 is related with the subtype (e.g. differentiating between β1- and β2-receptors). Discussion
To the best of our knowledge, this is the first study to examine the association between hypocretin receptor genes and AD. Additional studies in different populations are warranted in order to confirm our data. Genetic association studies are considered particularly useful in deciphering the genetic basis of complex diseases such as AD.
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Table 3. GF and AF of polymorphisms in AD patients and controls
rs2271933 G>A AD patients Male Female Total Controls Male Female Total
G/G
G/A
A/A
G, % A, %
50 (39.37) 60 (47.24) 17 (13.39) 0.63 0.37 105 (40.23) 121 (46.36) 35 (13.41) 0.63 0.37 155 (39.95) 181 (46.65) 52 (13.40) 0.63 0.37 30 (33.33) 43 (47.77) 17 (18.90) 0.57 0.43 63 (34.61) 89 (48.90) 30 (16.49) 0.59 0.41 93 (34.19) 132 (48.52) 47 (17.29) 0.58 0.42
rs10914456 C>T C/C T/C T/T C, % AD patients Male 42 (33.07) 67 (52.76) 18 (14.17) 0.6 Female 105 (40.23) 108 (41.38) 48 (18.39) 0.61 Total 147 (37.89) 175 (45.10) 66 (17.01) 0.61 Controls Male 31 (34.44) 40 (44.44) 19 (21.12) 0.56 Female 63 (34.61) 80 (43.96) 39 (21.43) 0.56 Total 94 (34.56) 120 (44.11) 58 (21.33) 0.57 rs4949449 G>T AD patients Male Female Total Controls Male Female Total rs2653349 G>A AD patients Male Female Total Controls Male Female Total rs3122156 T>G AD patients Male Female Total Controls Male Female Total
G/G
G/T
T/T
T, % 0.4 0.39 0.39 0.44 0.44 0.43
G, % T, %
43 (33.86) 64 (50.40) 20 (15.74) 0.59 0.41 92 (35.25) 134 (51.34) 35 (13.41) 0.6 0.4 135 (37.80) 198 (51.03) 55 (14.17) 0.63 0.37 30 (33.33) 44 (48.88) 16 (17.79) 0.57 0.43 58 (31.86) 88 (48.35) 36 (19.79) 0.56 0.44 88 (32.35) 132 (48.53) 52 (19.12) 0.56 0.44 G/G
G/A
A/A
G, % A, %
81 (63.78) 43 (33.86) 3 (2.36) 176 (67.43) 75 (28.73) 10 (3.84) 257 (66.24)a 118 (30.41)a 13 (3.35)
0.81 0.19 0.82 0.18 0.81b 0.19
52 (57.77) 104 (57.14) 156 (57.53)
0.75 0.25 0.74 0.26 0.74 0.26
T/T
31 (34.44) 7 (7.79) 63 (34.61) 15 (8.25) 94 (34.56) 22 (8.09) G/T
G/G
65 (51.18) 50 (39.37) 12 (9.45) 140 (53.64) 101 (38.7) 20 (7.66) 205 (52.84) 151 (38.92) 32 (8.24)
T, % G, % 0.71 0.29 0.73 0.27 0.73 0.27
48 (53.33) 33 (36.66) 9 (10.01) 0.72 0.28 98 (53.84) 67 (36.81) 17 (9.35) 0.72 0.28 146 (53.68) 100 (36.76) 26 (9.56) 0.73 0.27
Values are the number (%) of patients positive for each genotype. p values were calculated by the χ2 test from 3 × 2 (genotype) or 2 × 2 (allele) contingency tables. a GF χ2 = 5.77, p = 0.016; b AF χ2 = 6.72, p = 0.035.
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Gallone et al.: Is HCRTR2 a Genetic Risk Factor for Alzheimer’s Disease?
Table 4. Effects of the different polymorphisms on clinical features in patients with AD
rs2271933 G>A GG (n = 155) GA (n = 181) AA (n = 52) p (ANOVA) rs10914456 C>T CC (n = 147) CT (n = 175) TT (n = 66) p (ANOVA) rs4949449 G>T GG (n = 135) GT (n = 198) TT (n = 55) p (ANOVA) rs2653349 G>A GG (n = 257) GA (n = 118) AA (n = 13) p (ANOVA) rs3122156 T>G TT (n = 205) GT (n = 151) GG (n = 32) p (ANOVA) ApoE E2E2 (n = 0) E2E3 (n = 14) E3E3 (n = 125) E3E4 (n = 87) E4E4 (n = 12) p (ANOVA)
Age at sampling
Age of onset
MMSE score
76.16 ± 8.31 75.89 ± 8.20 76.00 ± 8.00 0.96
73.68 ± 7.93 73.23 ± 7.87 72.75 ± 8.36 0.85
19.19 ± 5.63 19.08 ± 5.22 19.20 ± 6.27 0.99
76.34 ± 8.122 75.53 ± 8.52 76.56 ± 7.54 0.64
73.60 ± 8.04 73.08 ± 7.97 73.58 ± 7.61 0.89
18.94 ± 5.84 19.17 ± 5.26 19.80 ± 5.50 0.74
76.14 ± 8.19 75.81 ± 8.37 76.48 ± 7.89 0.88
74.62 ± 7.30 72.67 ± 7.99 71.81 ± 9.20 0.13
18.51 ± 5.72 19.45 ± 5.23 19.19 ± 6.22 0.54
75.81 ± 8.90 76.83 ± 6.72 78.80 ± 4.39 0.46
72.94 ± 8.49 74.20 ± 6.91 73.63 ± 5.60 0.55
18.95 ± 5.63 19.38 ± 5.30 19.86 ± 5.95 0.82
75.80 ± 8.16 76.24 ± 8.45 76.22 ± 7.59 0.89
72.73 ± 8.07 73.74 ± 8.01 75.63 ± 5.84 0.33
18.61 ± 5.69 20.09 ± 5.11 17.56 ± 5.41 0.08
79.75 ± 3.57 76.40 ± 8.45 76.03 ± 7.04 73.17 ± 6.22 0.21
77.09 ± 4.41 74.40 ± 8.69 73.26 ± 7.18 68.20 ± 5.28 0.052
19.45 ± 5.08 19.63 ± 5.22 19.87 ± 5.37 21.75 ± 4.33 0.74
The results of our study show that the V308I polymorphism of the HCRTR2 gene is significantly associated with AD. Both allelic and genotypic frequencies of the HCRTR1 and HCRTR2 genes were similarly distributed between cases and controls. AF and GF in this study are in agreement with published data on the HapMap site (www.hapmap.ncbi.nlm.nih.gov) with regard to the distribution of the European population. Our results are supported by two different genome-wide association studies published on AD at GWAS Central (https://www.gwascentral.org/generegion/phenotypes). These studies (HGVPM72 and HGVPM576) reported a p value threshold –log p ≥ 3 in the 6p12.1 region in which the HCRT2 gene is located. The mechanism by which this SNP determines an increased risk is still unknown. It should, however, be taken into account that this polymorphism leads to an amino acidic change and, therefore, theoretically, the function of the protein could be affected. Data of the correlated mutation analysis and the participation of residue 308 in a binding pocket indicate that residue 308 might be at the dimer interface and that the Val308Ile polymorphism could influence the dimerization process of the protein. It might be argued that only the conserved amino acids are important for the basic function of the protein and that mutations of one of the amino acids may result in a loss of function. However, many of the
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amino acids that are correlated within a family are conserved in a subfamily, indicating that residues involved in correlated mutations may also have a similar role. From the analysis of the behaviour of mutated receptors belonging to other GPCR subfamilies, it appears that the basic function of the receptor involves the conserved residues, while the finer details of specificity involve the correlated residues. Genetic association studies are exposed to several biases (the systematic distortion of a statistic) such as phenotypic definition, adequate sample size of cases and controls and population stratification. The growing knowledge concerning the role of hypocretins/orexins in different neurological conditions has generated considerable interest in developing smallmolecule hypocretin receptor antagonists as a novel therapeutic strategy. Hypocretin antagonists, especially those that block Hcrtr1 or both Hcrtr1 and Hcrtr2 receptors, have been studied mainly as new drugs for sleep disorders. In experimental animal models, hypocretin/ orexin antagonists (almorexant, suvorexant) clearly promote sleep, and clinical results are encouraging [25–28]. However, the exact relationship between a partial loss of hypocretin and the occurrence of clinical symptoms remains unknown. In a rodent study, microinjections of prepro-hypocretin short interfering ribonucleic acids resulting in a 60% decrease in hypocretin messenger ribonucleic acid led to REM sleep alterations [29]. Another rodent study showed that lesioning 70% of hypocretin neurons results in both a decreased CSF hypocretin concentration and REM sleep disturbances [30]. This means that a partial loss of hypocretin functioning may lead to sleep disturbances, at least in rodents. In conclusion, according to these findings, the HCRTR2 1246G>A SNP is likely to be a risk factor for AD. The increased risk inferred is quite small, but in the context of a multi-factorial disease, the presence of this polymorphism may significantly contribute to influencing the susceptibility for AD by interacting with other unknown genetic or environmental factors. Nevertheless, further studies in larger populations are needed to draw definitive conclusions, together with the neuropathological confirmation of clinical diagnoses, and probably future studies should focus on the direct relationship between loss of hypocretin neurotransmission and clinical symptoms. Acknowledgments This work was supported by 2008 grants from the Regione, Ministero dell’Istruzione, dell’Università e della Ricerca Scientifica (MIUR) of Italy, the Italian Ministry of Health (Ricerca Corrente) and the Fondazione Monzino.
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