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Alzheimer’s
disease (AD) is a polygenic/complex disorder in which genomic, epigenomic,
cerebrovascular, metabolic, and environmental factors converge to define a
progressive neurodegenerative phenotype. Conventional anti-dementia drugs are
not cost-effective, and pharmacological breakthroughs have not been achieved
for the past 10 years. Major determinants of therapeutic outcome in AD include
age- and sex-related factors, pathogenic phenotype, concomitant disorders,
treatment modality and polypharmacy, and pharmacogenetics. Different categories
of genes are potentially involved in the pharmacogenetic network responsible
for drug efficacy and safety. Pathogenic, mechanistic, metabolic, transporter,
and pleiotropic genes represent the major genetic determinants of response to
treatment in AD. In pharmacogenetic studies, APOE-4 carriers are the worst responders and APOE-3 carriers are the best responders to conventional treatments.
Patients harboring a large (L) number of poly T repeats in intron 6 of the TOMM40 gene (L/L or S/L genotypes) in
haplotypes associated with APOE-4 are
the worst responders whereas patients with short (S) TOMM40 poly T variants (S/S genotype), and to a lesser extent S/VL
and VL/VL carriers, in haplotypes with APOE-3
are the best responders to treatment. Only 25% of the Caucasian population are
extensive metabolizers for trigenic haplotypes integrating CYP2D6-CYP2C19-CYP2C9 variants. Patients harboring CYP-related poor
(PM) and/or ultra-rapid (UM) geno-phenotypes display more irregular profiles in
drug metabolism than extensive (EM) or intermediate (IM) metabolizers. Among
111 pentagenic (APOE-APOB-APOC3-CETP-LPL)
haplotypes associated with lipid metabolism, carriers of the H26 haplotype
(23-TT-CG-AG-CC) exhibit the lowest cholesterol levels and patients with the
H104 haplotype (44-CC-CC-AA-CC) are severely hypercholesterolemic. Epigenetic
aberrations (DNA methylation, histone modifications, miRNA dysregulation) in
genes configuring the pharmacoepigenetic cascade also influence the
response/resistance to drugs. Consequently, novel strategies in drug
development, either preventive or therapeutic, for AD should take into
consideration these pharmacogenetic determinants for treatment optimization.
Keywords: Alzheimer’s disease, Anti-dementia drugs,
APOE, Atorvastatin, Cholesterol, Epigenetics, CYP haplotypes, LipoEsar,
Pharmacogenomics, Pharmacoepigenomics.
INTRODUCTION
Alzheimer’s disease (AD) is a major problem of health in developed countries and the most prevalent form of dementia, representing the 6th cause of death in the USA with and age-adjusted death rate of 25.4 per 100,000. Genomic, epigenomic, cerebrovascular, metabolic and environmental factors are potentially involved in the pathogenesis of AD. The age- and sex-related syndromic profile of AD reflects, at least, a tetravalent phenotype: (i) a neuropathological component (classic hallmarks: senile plaques, neurofibrillary tangles, neuritic desarborization, neuronal loss); (ii) a neurobehavioral component: cognitive deterioration, behavioral changes, functional decline; (iii) an age-related biological component (direct-, indirect-, and un-related biochemical, hematological and metabolic phenotypes); and (iv) gender-related phenotypes [1-3]. According to this heterogeneous, complex clinical picture, the therapeutic intervention in dementia is polymodal in order to modify the expression of all these complex phenotypes. AD patients present concomitant disorders including hypertension (20-30%), overweightness or obesity (20-40%), diabetes (20-25%), hypercholesterolemia (>40%), hypertriglyceridemia (20%); excess of urea (>80%), creatinine (6%) and uric acid (5%); alterations in transaminases (ASAT, ALAT, GGT) (>15%), alkaline phosphatase (14%), bilirubin (17%), and ions (>10%); deficits of iron (5%), ferritin (3%), folate (5%), and vitamin B12 (4%); thyroid dysfunction (5-7%), and reduced levels of RBC (3%), HCT (33%), and Hb (35%) [4]. Cardiovascular disorders (>40%), atherosclerosis (>60%), and different modalities of cerebrovascular damage (>60%) are also frequent among patients with AD. Most of these biochemical, hematological and metabolic anomalies exhibit gender differences and may contribute to accelerate the dementia process. The pharmacological treatment of these concomitant pathologies adds complexity and risks to the multifactorial therapeutic intervention in patients with dementia. Of major relevance is the treatment of diabetes, hypertension, dyslipidemia, and cardiovascular, cerebrovascular and neuropsychiatric disorders. The chronic treatment of these illnesses increases the risk of drug interactions and toxicity, aggravating the clinical condition of the demented patient. In this context, the incorporation of pharmacogenetic protocols into clinical practice is fundamental to minimize drug-drug interactions and ADRs, and to optimize the global therapeutic outcome, avoiding deleterious effects on mental function and cognition.
Major determinants of therapeutic outcome in AD include age- and
sex-related factors, pathogenic phenotype, concomitant disorders, treatment
modality and polypharmacy, and pharmacogenetics. Different categories of genes
are potentially involved in the pharmacogenetic network responsible for drug
efficacy and safety. Pathogenic, mechanistic, metabolic, transporter, and
pleiotropic genes represent the major genetic determinants of response to
treatment in AD [5,6]. By-products of these genes are integrated in transcriptomic,
proteomic and metabolic networks which are disrupted in AD and represent
potential targets for therapeutic intervention [6,7] (Figure 1).
TREATMENTS
AD patients may take 6-12 different drugs/day for the treatment of
dementia-related symptoms, including memory deterioration (conventional
anti-dementia drugs, neuroprotectants), behavioral changes (antidepressants,
neuroleptics, sedatives, hypnotics), and functional decline, or for the
treatment of concomitant pathologies (epilepsy, cardiovascular and cerebrovascular
disorders, parkinsonism, hypertension, dyslipidemia, anemia, arthrosis, etc).
Over 20% of dementia patients are current users of cardiovascular drugs. A high
throughput screening study assessed 1600 FDA-approved drugs for their ability
to modulate Aβ activity; 559 drugs of the 1600 had no effect on APP processing
or were toxic to neurons at the concentration tested, while 800 drugs could
reduce Aβ content by over 10% in primary neurons derived from Tg2576 mice,
among which, 184 drugs were able to reduce Aβ content by more than 30%; 241
drugs could potentially promote Aβ accumulation, including 26 drugs that could
increase the level of Aβ by over 30% [8]. The co-administration of several
drugs may cause side-effects and adverse drug reactions in over 60% of AD
patients, who in 2-10% of the cases require hospitalization. The prevalence of
potentially inappropriate medication (PIM) is around 50% in some European
cohorts. Cerebral vasodilators are the most widely used class of PIM,
accounting for 24.0% of all prescriptions, followed by atropinic drugs and long
half-life benzodiazepines. Atropinic drugs were associated with cholinesterase
inhibitors in 16% of patients. In over 20% of the patients, behavioral
deterioration and psychomotor function can be severely altered by polypharmacy
[9]. The principal causes of these iatrogenic effects are the inappropriate
combination of drugs, and the genomic background of the patient, responsible
for his/her pharmacogenomic outcome.
During the past 10 years, over 1,000 different compounds have been
studied as potential candidate drugs for the treatment of AD [6,7,10,11]. About
50% of these substances are novel molecules obtained from natural sources
[6,7]. The candidate compounds can be classified according to their pharmacological
properties and/or the AD-related pathogenic cascade to which they are addressed
to halt disease progression. In addition to the FDA-approved drugs since 1993
(tacrine, donepezil, rivastigmine, galantamine, memantine) (Table 1), most candidate strategies
fall into 6 major categories: (i) novel cholinesterase inhibitors and
neurotransmitter regulators, (ii) anti-Aβ treatments (APP regulators, Aβ
breakers, active and passive immunotherapy with vaccines and antibodies, β- and
γ-secretase inhibitors or modulators), (iii) anti-tau treatments, (iv)
pleiotropic products (most of them of natural origin), (v) epigenetic
intervention, and (vi) combination therapies [6,7,10,12].
During the 2002-2012 period, 413 AD trials were performed (124 Phase 1
trials, 206 Phase 2 trials, and 83 Phase 3 trials)(78% sponsored by
pharmaceutical companies). Registered trials addressed symptomatic agents
(36.6%), disease-modifying small molecules (35.1%) and disease-modifying
immunotherapies (18%), with a very high attrition rate (overall success rate:
0.4%; failure: 99.6%) [13]. During the past 15 years no new drugs have been
approved for the treatment of AD and the available drugs are not cost-effective
[14]. Therefore, the pharmacogenetics of AD is very limited, circumscribed to
cholinesterase inhibitors and memantine (Table
1), remaining stuck in a primitive stage of underdevelopment due to the
lack of novel therapeutic options. Although many studies on the
pharmacogenetics of AD have been published since the early 2000’s [15,16], many
of them are redundant and contradictory, focusing mainly on the APOE gene and, to a lesser extent, on
some CYP family genes and other minor
genes [17]. In this context, several considerations are pertinent regarding
further steps to be followed in order to achieve a more mature profile of AD
pharmacogenomics: (i) a better characterization of the roles played in drug
efficacy and safety by genes involved in the pharmacogenomic network is
necessary; (ii) since most genes are under the influence of the epigenetic
machinery, pharmacoepigenomics is becoming an attractive field which deserves
special attention; (iii) drug-drug interactions represent a problematic issue
in over 80% of AD patients (most patients require a multifactorial treatment
with different drugs); (iv) since the neurodegenerative process underlying AD
neuropathology starts 20-30 years before the onset of the disease, novel
therapeutics should be addressed to prevent premature neuronal death; (v)
specific biomarkers for AD are necessary in 3 different contexts: predictive
markers before disease onset, early diagnosis in initial stages, and drug
monitoring (in both preventive and/or therapeutic strategies); and (vi)
physicians should be aware of the usefulness of pharmacogenomics to prescribe
more accurately, avoid adverse reactions and optimize the limited therapeutic
resources available for the treatment of dementia [12,18].
PHARMACOGENOMICS
Pharmacogenomics accounts for 60-90% variability in pharmacokinetics
and pharmacodynamics. The modest effect (and toxicity) of current AD drugs (Table 1) is in part due to their
pharmacogenomic profile, since over 70% of AD patients are deficient
metabolizers [3,6,10]. The genes involved in the pharmacogenomic response to
drugs in dementia fall into five major categories:
(i) Genes
associated with disease pathogenesis: Mendelian mutations affect genes directly
linked to AD, including >30 mutations in the amyloid beta precursor protein
(APP) gene (21q21)(AD1); >160
mutations in the presenilin 1 (PSEN1)
gene (14q24.3)(AD3); and >10 mutations in the presenilin 2 (PSEN2) gene (1q31-q42)(AD4) [19-23]. PSEN1 and PSEN2 are important determinants of γ-secretase activity
responsible for proteolytic cleavage of APP and NOTCH receptor proteins. Mendelian
mutations are very rare in AD (1:1000). Mutations in exons 16 and 17 of the APP gene appear with a frequency of
0.30% and 0.78%, respectively, in AD patients. Likewise, PSEN1, PSEN2, and microtubule-associated protein Tau (MAPT) (17q21.1) mutations are present in
less than 2% of the cases. Mutations in these genes confer specific phenotypic
profiles to patients with dementia: amyloidogenic pathology associated with APP, PSEN1
and PSEN2 mutations and tauopathy
associated with MAPT mutations
representing the two major pathogenic hypotheses for AD [19-25].
Multiple polymorphic risk variants can increase neuronal vulnerability
to premature death. There are at least 695 genes potentially associated with
AD, of which the top ten are: APOE
(19q13.2), BIN1 (2q14), CLU (8p21-p12), ABCA7 (19p13.3), CR1
(1q32), PICALM (11q14), MS4A6A (11q12.1), CD33 (19q13.3), MS4A4E
(11q12.2), and CD2AP (6p12) [10,23].
Potentially defective genes associated with AD represent about 1.39% (35,252.69
Kb) of the human genome, which is integrated by 36,505 genes (3,095,677.41 Kb).
The highest number of AD-related defective genes concentrate on chromosomes 10
(5.41%; 7,337.83 Kb), 21 (4.76%; 2,289.15 Kb), 7 (1.62%; 2,584.26 Kb), 2
(1.56%; 3,799.67 Kb), 19 (1.45%; 854.54 Kb), 9 (1.42%; 2,010.62 Kb), 15 (1.23%;
1,264.4 Kb), 17 (1.19%; 970.16 Kb), 12 (1.17%; 1,559.9 Kb), and 6 (1.15%;
1,968.22 Kb) [6]. Among susceptibility genes, the apolipoprotein E (APOE) gene (AD2) is the most prevalent
as a risk factor for AD, especially in those subjects harboring the APOE-4 allele, whereas carriers of the APOE-2 allele might be protected against
dementia [19]. Polymorphic variants in other genes (GRB-associated binding
protein 2 (GAB2), TLR9 rs187084 variant homozygote GG, LRRK2 R1628P variant) might also be
protective [6]. Ten novel private pathogenic copy number variations (CNVs) in
10 early-onset familial Alzheimer's disease (EO-FAD) families overlapping a set
of genes (A2BP1, ABAT, CDH2, CRMP1,
DMRT1, EPHA5, EPHA6, ERMP1, EVC, EVC2, FLJ35024 and VLDLR) have also been identified [26].
(ii) Genes associated with the mechanism of action of drugs (enzymes,
receptors, transmitters, messengers).
(iii) Genes associated with drug metabolism: (a) phase I reaction
enzymes: alcohol dehydrogenases (ADH1-7),
aldehyde dehydrogenases (ALDH1-9),
aldo-keto reductases (AKR1A-D), amine
oxidases (MAOA, MAOB, SMOX), carbonyl
reductases (CBR1-4), cytidine
deaminase (CDA), cytochrome P450
family (CYP1-51, POR, TBXAS1),
cytochrome b5 reductase (CYB5R3),
dihydropirimidine dehydrogenase (DPYD),
esterases (AADAC, CEL, CES1, CES1P1,
CES2, CES3, CES5A, ESD, GZMA, GZMB, PON1, PON2, PON3, UCHL1, UCHL3),
epoxidases (EPHX1-2),
flavin-containing monooxygenases (FMO1-6),
glutathione reductase/peroxidases (GPX1-7,
GSR), short-chain dehydrogenases/reductases (DHRS1-13, DHRSX, HSD11B1, HSD17B10, HSD17B11, HSD17B14), superoxide
dismutases (SOD1-2), and xanthine
dehydrogenase (XDH); and (b): phase
II reaction enzymes: amino acid transferases (AGXT, BAAT, CCBL1), dehydrogenases (NQO1-2, XDH), esterases (CES1-5),
glucuronosyl transferases (UGT1-8),
glutathione transferases (GSTA1-5, GSTK1,
GSTM1-5, GSTO1-2, GSTP1, GSTT1-2, GSTZ1, GSTCD, MGST1-3, PTGES), methyl
transferases (AS3MT, ASMT, COMT, GNMT,
GAMT, HNMT, INMT, NNMT, PNMT, TPMT), N-acetyl transferases (ACSL1-4, ACSM1, ACSM2B, ACSM3, AANAT, GLYAT, NAA20, NAT1-2, SAT1),
thioltransferase (GLRX), and sulfotransferases (CHST2-13, GAL3ST1, SULT1A1-3, SULT1B1, SULT1C1-4, SULT1E1, SULT2A1,
SULT2B1, SULT4A1, SULT6B1, CHST1).
(iv) Genes associated with drug transporters: In humans there are 49 ABC transporter genes and the multidrug
resistance associated proteins (MRP1/ABCC1, MRP2/ABCC2, MRP3/ABCC3, MRP4/ABCC4,
MRP5/ABCC5, MRP6/ABCC6, MRP7/ABCC10, MRP8/ABCC11 and MRP9/ABCC12) which belong to the ABCC family integrated by 13 members. Other genes encoding
transporter proteins are genes of the solute carrier superfamily (SLC) and solute carrier organic (SLCO) transporter family, responsible
for the transport of multiple endogenous and exogenous compounds.
(v) Pleiotropic genes involved in multifaceted cascades and metabolic
reactions [5,6,27].
All these genes are under the influence of the epigenetic machinery
conditioning their expression and the efficiency of their drug-metabolizing
products (enzymes, transporters) [28-30].
Genetic determinants
of the pharmacogenetic outcome with conventional neuroprotectants and acetyl
cholinesterase inhibitors.
Although the APP, PSEN1, PSEN2
and MAPT genes are considered major
pathogenic genes for AD and classic tauopathies [23], mutations in these genes
represent less than 5% of the AD population and, consequently, their influence
on AD pharmacogenetics associated with conventional anti-dementia drugs is
quantitatively negligible; not so in the case of immunotherapy addressing Aβ
deposition. Most anti-AD vaccines (active and passive immunization) are based
on transgenic models with APP, PSEN1 and
PSEN2 mutants [31,32]. In general,
most pharmacogenetic studies in AD have been performed with susceptibility
genes (APOE) and metabolic genes (CYPs) [6,10].
-APOE-TOMM40
To date, the most influential gene in AD pharmacogenetics is the APOE gene [2,6,10,27,33]. APOE is a pleiotropic gene with
multifaceted activities in physiological and pathological conditions, and the
presence of the APOE-4 allele is
determinant in AD pathogenesis [19]. APOE-4
may influence AD pathology by interacting with APP metabolism and Aβ
accumulation, enhancing hyperphosphorylation of tau protein and neurofibrillary
tangle formation, reducing choline acetyltransferase activity, increasing
oxidative processes, modifying inflammation-related neuroimmunotrophic activity
and glial activation, altering lipid metabolism, lipid transport and membrane
biosynthesis in sprouting and synaptic remodeling, and inducing neuronal
apoptosis and premature neuronal death [5,19]. Multiple studies over the past
two decades have demonstrated that APOE
variants may affect the therapeutic response to anti-dementia drugs
[3,5,6,10,15,16,19,27,33-35]. At least 20 major phenotypic features illustrate
the biological disadvantage of APOE-4
homozygotes and the potential consequences that these patients may experience
when they receive pharmacological treatment for AD and/or concomitant
pathologies [5,6,15,19,33,34,38].
In over 100 clinical trials for dementia, APOE has been used as the only gene of reference for the
pharmacogenomics of AD. Several studies indicate that the presence of the APOE-4 allele differentially affects the
quality and extent of drug responsiveness in AD patients treated with
cholinergic enhancers, neuroprotective compounds, endogenous nucleotides,
immunotrophins, neurotrophic factors, combination therapies and other drug
categories [1,5,6,35-40]; however, controversial results are frequently found
due to methodological problems, study design, and patient recruitment in
clinical trials. The major conclusion in most studies is that APOE-4 carriers are the worst responders
to conventional treatments [5,6,10]. When APOE
and CYP2D6 genotypes are integrated
in biogenic clusters and the APOE+CYP2D6-related
therapeutic response to a combination therapy is analyzed in AD patients, it
becomes clear that the presence of the APOE-4/4
genotype is able to convert pure CYP2D6*1/*1
extensive metabolizers into full poor responders to conventional treatments,
indicating the existence of a powerful influence of the APOE-4 homozygous genotype on the drug-metabolizing capacity of
pure CYP2D6 extensive metabolizers
[3]. In addition, a clear accumulation of APOE-4/4
genotypes is observed among CYP2D6 poor
and ultra-rapid metabolizers [3].
Adjacent to the APOE locus
(19q13.2) and in linkage disequilibrium with APOE is the TOMM40 gene.
A poly T repeat in an intronic polymorphism (rs10524523) (intron 6) in the TOMM40 gene, which encodes an outer
mitochondrial membrane translocase involved in the transport of Aβ and other
proteins into mitochondria, has been implicated in AD [41-54]. APOE-TOMM40 genotypes have been shown to
modify disease risk and age at onset of symptoms [42-47,55]. The rs4420638 at
the TOMM40/APOE/APOC1 gene locus is
associated with longevity [56,57]. The APOE-TOMM40
genomic region is associated with cognitive aging [58] and with pathological
cognitive decline [59]. There are 3 allele groups for rs10524523 ('523'), based
on the number of 'T'-residues: 'Short' (S, T ≤ 19), 'Long' (L, 20 ≤ T ≤ 29) and
'Very Long' (VL, T ≥ 30) [49]. Longer lengths of rs10524523 are associated with
a higher risk for late-onset AD (LOAD) [43-47]. Intronic poly T (rs10524523)
within this region affects expression of the APOE and TOMM40 genes in
the brain of patients with LOAD [60]. The 523 VL poly T shows higher expression
than the S poly T, indicating that the 523 locus may contribute to LOAD
susceptibility by modulating the expression of TOMM40 and/or APOE
transcription [60]. S/VL and VL/VL are the only TOMM40 poly T genotypes which interact with all major APOE
genotypes; in contrast, the APOE-4/4-TOMM40-L/L
association is unique, representing approximately 30% of APOE-4/4 carriers [61] (Figure
2).
The first pharmacogenetic study of the APOE-TOMM40
region in AD patients receiving a multifactorial treatment revealed that: (i) APOE-4 carriers are the worst responders
(Figure 3-4) and APOE-3 carriers are the best responders
to conventional treatments (Figure 3-4);
(ii) TOMM40 poly T-S/S carriers are
the best responders (Figure 3-4),
VL/VL and S/VL carriers are intermediate responders, and L/L carriers are the
worst responders to treatment (Figure
3-4); (iii) patients harboring a large (L) number of poly T repeats in
intron 6 of the TOMM40 gene (L/L or
S/L genotypes) in haplotypes associated with APOE-4 are the worst responders to treatment; (iv) patients with
short (S) TOMM40 poly T variants (S/S
genotype), and to a lesser extent S/VL and VL/VL carriers, in haplotypes with APOE-3 are the best responders to
treatment; and (v) in 100% of the cases, the L/L genotype is exclusively
associated with the APOE-4/4 genotype
(Figure 2), and this haplotype
(4/4-L/L) is probably responsible for early onset of the disease, a faster
cognitive decline, and a poor response to different treatments [4,61].
Other recent pharmacogenetic studies with pathogenic or mechanistic
genes indicate that the response to Acetylcholinesterase inhibitors (AChEIs) is
associated with 2 single nucleotide polymorphisms (SNPs) in the intronic region
of CHAT rs2177370 and rs3793790 [62].
The CHRNA7 T allele (rs6494223) also
associates with a better response to AChEIs and there is further confirmation
that APOE-4 carriers are the worst
responders to conventional AChEIs [63].
-CYPs
Over 70% of AD patients are deficient metabolizers for the CYP2D6/2C19/2C9 trigenic cluster; and
for the CYP2D6/2C19/2C9/3A4
tetragenic cluster, more than 80% of the patients exhibit a deficient
metabolizer geno-phenotype [3]. These four CYP
genes encode enzymes responsible for the metabolism of 60-80% of drugs of
current use, showing ontogenic-, age-, sex-, circadian- and ethnic-related
differences [5,6,33,64]. According to the database of the World Guide for Drug
Use and Pharmacogenomics [38], 982 drugs are CYP2D6-related: 371 drugs are
substrates, over 300 drugs are inhibitors, and 18 drugs are CYP2D6 inducers.
Over 600 drugs are CYP2C9-related, 311 acting as substrates (177 are major
substrates, 134 are minor substrates), 375 as inhibitors (92 weak, 181
moderate, and 102 strong inhibitors), and 41 as inducers of the CYP2C9 enzyme
[38]. Nearly 500 drugs are CYP2C19-related, 281 acting as substrates (151 are
major substrates, 130 are minor substrates), 263 as inhibitors (72 weak, 127
moderate, and 64 strong inhibitors), and 23 as inducers of the CYP2C19 enzyme
[38]. The CYP3A4/5 enzyme metabolizes over 1900 drugs, 1033 acting as
substrates (897 are major substrates, 136 are minor substrates), 696 as
inhibitors (118 weak, 437 moderate, and 141 strong inhibitors), and 241 as
inducers of the CYP3A4 enzyme [38].
The distribution and frequency of CYP2D6
genotypes are very similar in the general population (GP) (N=3232) and in AD
(N=1289), with the exception of the CYP2D6-*3/*4
genotype (p<0.05) which is absent in AD samples (Figure 5). In the GP, CYP2D6 extensive metabolizers (EMs) account
for 58.85%, whereas intermediate metabolizers (IMs) account for 31.11%, poor
metabolizers (PMs) 4.49%, and ultra-rapid metabolizers (UMs) 5.55% [6,10] (Fig. 5). In AD, EMs, IMs, PMs, and UMs
are 57.54%, 31.01%, 5.49%, and 5.96%, respectively. There is an accumulation of
AD-related genes of risk in PMs and UMs. EMs and IMs are the best responders,
and PMs and UMs are the worst responders to a combination therapy with AChEIs,
neuroprotectants, and vasoactive substances. The pharmacogenetic response in AD
appears to be dependent upon the networking activity of genes involved in drug
metabolism and genes involved in AD pathogenesis [5,6,19,33,34,65-67]. By
phenotypes, in the GP, CYP2C9-PMs represent 4.82%, IMs 33.83%, and EMs 61.35%.
In AD, PMs, IMs, and EMs are 4.76%, 34.87%, and 60.37%, respectively [6,38] (Figure 6).
The frequencies of the CYP2C19 geno-phenotypes in the GP are:
CYP2C19-EMs 74.11%, CYP2C19-IMs 24.43%, and CYP2C19-PMs 1.46% (Figure 7). EMs, IMs, and PMs account
for 75.41%, 23.56%, and1.03%, respectively, in AD [6,38] (Figure 7). Concerning CYP3A4/5
polymorphisms in AD, 83.84% of the cases are EMs (CYP3A5*3/*3), 14.62% are IMs (CYP3A5*1/*3),
and 1.54% are RMs (CYP3A5*1/*1) [6] (Figure 8), whereas in the GP, EMs, IMs
and RMs represent 82.17%, 16.48%, and 1.35%, respectively (Figure 8).
Tetragenic haplotypes integrating CYP2D6,
CYP2C9, CYP2C19 and CYP3A4/5
variants yield 156 genotypes (Figure 9).
The most frequent haplotype is H3 (1/1-1/1-1/1-3/3) (20.87%), representing full
extensive metabolizers, and only 17 haplotypes exhibit a frequency higher than
1% in the Spanish population (Figure 10).
In addition to H3, the most frequent haplotypes (>2%) are H55
(1/4-1/1-1/1-1/3)(8.41%), H26 (1/1-1/2-1/1-3/3)(8.07%), H4
(1/1-1/1-1/2-3/3)(8.07%), H58 (1/4-1/1-1/2-3/3)(3.99%), H72
(1/4-1/2-1/1-3/3)(3.82%), H2 (1/1-1/1-1/1-1/3)(3.74%), H9 (1/1-1/1-1/3-3/3)(3.57%),
and H38 (1xN/1-1/1-1/1-3/3)(2.46%) (Figure
10). This indicates that in the Spanish GP about 80% of the population is
deficient for the biotransformation of current drugs which are metabolized via
CYP2D6-2C9-2C19-3A4 enzymes.
Most anti-dementia drugs are metabolized via CYP enzymes. Donepezil is
a major substrate of CYP2D6, CYP3A4, ACHE, and UGTs, inhibits ACHE and BCHE,
and is transported by ABCB1 [2,6,17,33,34,38,65,67-69] (Table 1). CYP2D6 variants affect donepezil efficacy and safety in
AD [2,6,17,33,34,38,65,66,69]. The common variant rs1080985 of CYP2D6 is associated with poor response
to donepezil [70,71]. A higher frequency of mutated CYP2D6 allele *2A was found in responder than in non-responder
patients (75.38 % vs 43.48 %) [72]. In an Italian study, 67% of patients were
responders and 33% were non-responders to donepezil treatment, with abnormal
enzymes accumulating in responders [73]. Chinese AD patients with the mutant
allele CYP2D6*10 may respond better
(58% responders) to donepezil than those with wild allele CYP2D6*1 [74]. In contrast, other studies revealed that CYP2D6-PMs
and UMs tend to be poor responders to conventional doses of donepezil as
compared to EMs and IMs [2,6,17,33,34,38,69,75-77].
In Italian patients, no association was found between CYP3A4 or CYP3A5 genotypes and plasma donepezil concentrations, or between
genotypes and clinical response. The most common ABCB1 haplotypes were 1236C/2677G/3435C (46%) and 1236T/2677T/3435T
(41%), and patients homozygous for the T/T/T haplotype had lower plasma
donepezil concentration-to-dose ratios and better clinical response than
patients with other genotypes [78]. In Brazilian patients treated with AChEIs
the response rate was 27.8%, with no apparent effect of APOE and/or CYP2D6 polymorphic variants [79].
The effects of galantamine are potentially influenced by APOE, APP, ACHE, BCHE, CHRNA4, CHRNA7,
CHRNB2 variants. This drug is a major substrate of CYP2D6, CYP3A4, and
UGT1A1, and an inhibitor of ACHE and BCHE [38,68,69,80-82] (Table 1). Major metabolic pathways are
glucuronidation, O-demethylation, N-demethylation, N-oxidation, and
epimerization [83]. Galantamine is extensively metabolized by the enzymes
CYP2D6 and CYP3A and is a substrate of the P-gp. CYP2D6 variants are
determinant for galantamine pharmacokinetics. CYP2D6-PMs exhibit higher
dose-adjusted galantamine plasma concentrations than heterozygous and homozygous
CYP2D6-EMs [84]; however, these pharmacokinetic changes might not substantially
affect pharmacodynamics [85]. The co-administration of galantamine with
paroxetine (a CYP2D6 strong inhibitor), ketoconazole (a CYP3A4 strong
inhibitor) and erythromycin increases its bioavailability [86,87]. Interaction
with foods and nutritional components may alter galantamine bioavailability and
therapeutic effects [88].
APOE, APP, CHAT, ACHE, BCHE,
CHRNA4, CHRNB2 and
MAPT variants may affect rivastigmine
pharmacokinetics and pharmacodynamics, but CYP enzymes are not involved in the
metabolism of rivastigmine [38,68,69,86,89]. UGT2B7-PMs show higher
rivastigmine levels with a poor response to treatment [90].
ACHE, ABCB4, BCHE, CHRNA4, CHRNB2,
APOE, MTHFR, CES1, LEPR, GSTM1 and GSTT1 variants may affect
the therapeutic and toxic effects of tacrine (the first AChEI introduced in
1993 and withdraw years later due to hepatotoxicity). Tacrine is a major
substrate of CYP1A2 and CYP3A4, a minor substrate of CYP2D6, and is transported
via SCN1A and ABCB4. Tacrine is an inhibitor of ACHE, BCHE, and CYP1A2 [38].
Both tacrine and some tacrine-hybrids may cause an induction of CYP1A1, 2B1 and
3A2 expression [91]. Tacrine is associated with transaminase elevation in up to
50% of patients. The mechanism of tacrine-induced liver damage is influenced by
genetic factors. The strongest association was found between alanine
aminotransferase levels and three ABCB4
SNPs [92].
Memantine is an N-Methyl-D-Aspartate (NMDA) receptor antagonist which
binds preferentially to NMDA receptor-operated cation channels; it may act by
blocking actions of glutamate, mediated in part by NMDA receptors, and is also
an antagonist of GRIN2A, GRIN2B, GRIN3A, HTR3A and CHRFAM7A. Several pathogenic
(APOE, PSEN1, MAPT) and mechanistic
gene variants (GRIN2A, GRIN2B, GRIN3A,
HTR3A, CHRFAM7A, c-Fos, Homer1b and PSD-95)
may influence its therapeutic effects. Memantine is a strong inhibitor of
CYP2B6 and CYP2D6, and a weak inhibitor of CYP1A2, CYP2A6, CYP2C9, CYP2C19,
CYP2E1, and CYP3A4 [38,69,93]. In human liver microsomes (HLM), memantine
inhibits CYP2B6 and CYP2D6 activities, decreases CYP2A6 and CYP2C19 activities,
and has no effect on CYP1A2, CYP2E1, CYP2C9, or CYP3A4 activities [94]. The
co-administration of memantine with CYP2B6 substrates elicits a 65% decrease in
its metabolism. In clinical studies, NR1I2
rs1523130 was identified as the unique significant genetic covariate for
memantine clearance, with carriers of the NR1I2
rs1523130 CT/TT genotypes presenting a 16% slower memantine elimination than
carriers of the CC genotype [95].
Transporters
Polymorphic variants in genes encoding transporter proteins may affect
drug metabolism, brain penetrance and accessibility to neuronal/glial targets,
and drug resistance [96-98]. Of special importance in AD are the ABC and SLC family genes [98]. ABC genes (ABCB1, ABCC1, ABCG2), and other genes of this family encode
proteins which are essential for drug metabolism and transport. Mutations in ABC transporters influence pathogenesis
and therapeutics of brain disorders [98,99]. The multidrug efflux transporters
(P-gp1/MDR1, multidrug-resistance associated protein 4 (MRP4), breast cancer
resistance protein (BCRP)), are located on endothelial cells lining brain
vasculature and play important roles in limiting movement of substances into
and enhancing their efflux from the brain.
ABCB1 is one of the most important drug
transporters in the brain. Over 1270 drugs have been reported to be associated
with the ABCB1 transporter protein (P-gp), of which 490 are substrates, 618 are
inhibitors, 182 are inducers, and 269 additional compounds which belong to
different pharmacological categories of products with potential Abcb1
interaction [38]. The ABCB1 gene has
116 polymorphic sites in Caucasians and 127 in African-Americans, with a minor
allele frequency greater than 5%. Common variants are 1236C>T, 2677G>A/T
and 3435C>T, and the ABCB1*13
haplotype involves the 1236, 2677 and 3435 (TTT) SNPs and 3 intronic SNPs (in
intron 9, 13, and 14) [38]. The ABCB1 C1236T, G2677T/A and C3435T SNPs
influence blood-brain barrier (BBB) P-glycoprotein function. AD patients with
one or more T in C1236T, G2677T and C3435T have significantly higher binding
potential values than patients without a T. Genetic variations in ABCB1 might contribute to the
progression of Aβ deposition in the brain [100] and some ABCB1 SNPs (C1236T in exon 12, G2677T/A in exon 21 and C3435T in
exon 26) and inferred haplotypes might represent novel biomarkers of AD [101].
ABCB1 directly transports Aβ from the brain into the blood circulation, whereas
the cholesterol transporter ABCA1 neutralizes Aβ aggregation capacity in an APOE-dependent manner, facilitating
subsequent Aβ elimination from the brain [102]. Some ABCB1 variants are frequent in AD cases over 65 years of age and
among females. This association of ABCB1
2677G>T (rs2032582) is more pronounced in APOE4-negative cases [100].
Some other ABCs have shown
potential association with AD [98,103]. The G allele of the ABCA7 rs115550680 SNP is associated with
AD in Europeans. The effect size for the SNP in ABCA7 was comparable with that of the APOE ε4-determining SNP rs429358 [104]. ABCG2 is involved in Aβ transport and is up-regulated in AD brains.
The ABCG2 gene (C421A; rs2231142) (ABCG2 C/C genotype) is associated with
AD and the ABCG2 C/C genotype and the
APOE ε4 allele may exert an
interactive effect on AD risk [105]. Also of importance for AD pharmacogenomics
are transporters encoded by genes of the solute carrier superfamily (SLC) and
solute carrier organic (SLCO) transporter family, responsible for the transport
of multiple endogenous and exogenous compounds, including folate (SLC19A1), urea (SLC14A1-2), monoamines (SLC29A4,
SLC22A3), aminoacids (SLC1A5, SLC3A1,
SLC7A3, SLC7A9, SLC38A1, 4-5, 7, SLC43A2, SLC45A1), nucleotides (SLC29A2-3), fatty acids (SLC27A1-6), neurotransmitters (SLC6A2 (noradrenaline transporter), SLC6A3 (dopamine transporter), SLC6A4 (serotonin transporter, SERT), SLC6A5-6, 9, 11, 12, 14-19), glutamate (SLC1A6-7), and others [98,106]. Some organic anion transporters
(OAT), which belong to the solute carrier (SLC) 22A family, are also expressed
at the BBB, and regulate the excretion of endogenous and exogenous organic
anions and cations [107]. The transport of amino acids and di- and tri-peptides
is mediated by a number of different transporter families, and the bulk of
oligopeptide transport is attributable to the activity of members of the SLC15A
superfamily (SLC15A1-2, SLC15A2, SLC15A3-4). ABC and SLC transporters expressed
at the BBB may cooperate to regulate the passage of different molecules into
the brain [6,10,27,108].
Genetic determinants
associated with lipid metabolism and cholesterol response to hypolipemic drugs
in hypercholesterolemic patients with AD.
Among hundreds of genes potentially involved in AD pathogenesis and
concomitant disorders (cardiovascular and cerebrovascular disorders,
hypercholesterolemia), at least 4 categories of genes deserve special
attention: (i) genes associated with lipid metabolism: APOB (OMIM 107730; rs693 [7545C>T]; risk SNP 7545T)(participates
in the atherogenic process in cooperation with VLDL, IDL and LDL); APOC3 (OMIM 107720; rs5128 [3175G>C,
S1/S2]; risk SNP 3175G (S2)) (associated with triglyceride levels; inhibits the
activity of lipoprotein lipase and hepatic lipase); APOE (OMIM 107741; rs429358/rs7412 [112T>C/158T>C, E2, E3,
E4]; risk SNP 112C/158C (E4)) (encodes apolipoprotein E, involved in the
catabolism of triglyceride-rich lipoproteins and cholesterol homeostasis); CETP (OMIM 118470; rs708272 [+279G>A,
B1/B2]; risk SNP +279G (B1))(contributes to eliminate cholesterol from tissues
via reverse cholesterol transport); and LPL
(OMIM 609708; rs328 [1421C>G, S474X]; protective SNP 1421G)(hydrolyzes
triglycerides which are part of VLDL and chylomicrons and removes lipoproteins
from circulation)[28,109-112]; (ii) genes associated with endothelial function
and hypertension: NOS3 (OMIM 163729; rs1799983 [894G>T]; risk SNP 894T)
(encodes nitric oxide synthase 3 which synthesizes nitric oxide (NO) from the
amino acid arginine); ACE (OMIM
106189; rs4332 [547C>T]; risk SNP 547T) (hydrolyzes angiotensin I to
angiotensin II, a potent vasopressor and aldosterone-stimulating peptide, and
inactivates bradykinin, a potent vasodilator); and AGT (OMIM 1906150; rs699 [9543A>G, T174M]; risk SNP 174M; rs4762
[9360G>A, M235T]; risk SNP 235T) (encodes angiotensinogen, which is
converted into angiotensin I by renin) [38,113-116]; (iii) genes associated
with immune function and inflammation: IL1B
(OMIM 147720; rs1143634 [3954C>T]; risk SNP 3954T) (encodes interleukin-1β, which
is involved in the modulation of the inflammatory reaction in thrombus
formation); IL6 (OMIM 147620;
rs1800795 [-174G>C]; risk SNP -174C; rs1800796 [-573G>C]; risk SNP -573C)
(encodes interleukin-6, a pleiotropic cytokine involved in the regulation of
the acute phase reaction, immune response, hematopoiesis, and platelet
production); IL6R (OMIM 147880;
rs8192284 [1510A>G]; risk SNP 1510C) (encodes a subunit of the IL6 receptor
complex); and TNFA (OMIM 191160;
rs1800629 [-308G>A]; risk SNP -308A) (encodes tumor necrosis factor, a
proinflammatory cytokine that influences lipid metabolism, coagulation, insulin
resistance and endothelial function) [38,117-127]; and (iv) genes associated
with thrombosis and coagulation: F2
(OMIM 17693; rs1799983 [20210G>A]; risk SNP 2021A) (encodes Coagulation
Factor 2 (Prothrombin), involved in blood clotting); F5 (OMIM 227400; rs6025 [1691G>A]; risk SNP 1691A) (encodes
Factor V Leiden, an important factor involved in blood coagulation); and MTHFR (OMIM 607093; rs1801133
[677C>T]; risk factor 677T; rs1801131 [1298A>C]; risk SNP 1298A) (encodes
methylenetetrahydrofolate reductase, an enzyme that catalyzes the conversion of
5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, a co-substrate for the
re-methylation of homocysteine to methionine) [38,128-132].
Although differences in genotype distribution and frequencies of all
these genes between patients with AD and control subjects are negligible,
except in the case of APOE [133] (Figure 11) some of them may influence
the pharmacogenetic outcome in the treatment of major risk factors for
dementia, such as hypercholesterolemia, cardiovascular disorders and
hypertension [133-137]. Furthermore,
many of these genes interact in pathogenic cascades contributing to alter brain
cholesterol and Aβ metabolism, subsequently accelerating neuronal death in AD.
PHARMACOGENETICS
OF HYPERCHOLESTEROLEMIA IN ALZHEIMER’S DISEASE
Alterations in cholesterol (CHO) metabolism are involved in AD
pathogenesis and over 40% of AD patients are hypercholesterolemic. Cognitive
deterioration shows a clear age-dependent profile (Figure 12), with an average decline on 3-5 points/year (MMSE
score); however, total CHO levels do not appear to affect mental deterioration
in AD (Figure 13). Blood lipid
levels also show a moderate age-dependent profile (Figure 14). In the GP, CHO levels tend to increase with age
reaching a plateau at 60-70 years of age, declining thereafter; however, CHO
levels in AD tend to diminish in an age-related fashion (Figure 15).
In a group of AD patients (N=920) recruited for pharmacogenomic studies
treated with a multifactorial therapy for one year [61], we evaluated the
effects of Sardilipin (E-SAR-94010; LipoEsar®) (500 mg/day) (nutraceutical with
lipid-lowering effects and anti-atherosclerotic and neuroprotective properties,
Patent ID: P9602566) [6,38,138] (whole group), and atorvastatin (10
mg/day)(patients with hypercholesterolemia >220 mg/dL) (43.48%) (first month
of treatment) on lipid metabolism (total-cholesterol, HDL-cholesterol, LDL-cholesterol,
triglycerides) according to the APOE
and CYP genotypes of the patients.
From these studies we obtained interesting results which enable us to infer
some conclusions with important repercussions on the pharmacogenetics of AD:
(i) Body Mass Index (BMI) is not affected by total cholesterol (T-CHO) or
LDL-CHO; however, there is a clear positive correlation between BMI and
triglyceride (TG) levels and an inverse correlation between BMI and HDL-CHO.
(ii) Liver transaminase activity is important for lipid metabolism. ASAT, ALAT
and GGT exhibit different correlation patterns in relation to lipid levels.
ASAT shows an inverse correlation with T-CHO and LDL-CHO; ALAT and GGT
activities increase in parallel with TG levels, and tend to show an inverse
correlation with HDL-CHO. (iii) Hypercholesterolemic females and males with AD
show a similar response to the combination of Atorvastatin + LipoEsar, but more
females (60%) are hypercholesterolemic than males (<20%). (iv) CHO levels
are APOE-dependent. APOE-4/4 carriers
exhibit the highest CHO levels. APOE-2/3,
APOE-3/4 and APOE-4/4 carriers
experience a gradual age-dependent decrease in CHO levels. (v) The therapeutic
response of CHO to Atorvastatin + LipoEsar is APOE-dependent. APOE-3/3
and APOE-3/4 carriers are the best
responders and APOE-2/4 and APOE-4/4 carriers are the worst
responders. (vi) Basal CHO levels are similar in CYP2D6-EMs, IMs, PMs and UMs.
CYP2D6-EMs and IMs show a significant decrease in CHO levels in response to
Atorvastatin + LipoEsar, whereas PMs and UMs exhibit a poorer CHO-lowering
effect. (vii) Basal CHO levels are higher in CYP2C9-IMs than in EMs. CYP2C9-EMs
and IMs effectively respond to Atorvastatin + LipoEsar, with a significant
reduction in CHO levels, and CYP2C9-PMs do not respond. (viii) Basal CHO levels
are non-significantly higher in CYP2C19-EMs and IMs than in PMs. CYP2C19-EMs
and IMs significantly respond to Atorvastatin + LipoEsar, and PMs do not show
any effect. (ix) CYP3A4/5-EMs show a significant decrease in CHO levels after one
month of treatment with Atorvastatin + LipoEsar. This response is similar for
LDL-CHO in EMs and IMs. In hypercholesterolemic patients, over 80% of EMs
respond to 20 mg of Atorvastatin + 500 mg of LipoEsar, with an almost complete
normalization of CHO levels. The effect in IMs is spectacular, with over 90% of
the patients experiencing a drastic reduction in CHO levels, 50% of them
entering into a condition of iatrogenic hypocholesterolemia; and 60% of RMs do
not respond at all.
In a larger study with 1345 hypercholesterolemic AD patients (CHO>220
mg/dL) (Figure 16) we investigated
the pharmacogenetics of cholesterol response to the hypolipemic compounds
Atorvastatin + LipoEsar for one month. In the whole sample, the response rate
(RR) was 78.95% responders (CHO
In a selected group of 933 AD patients we constructed a pentagenic
haplotype integrating all possible variants of the APOE+APOB+EPOC3+CETP+LPL genes and identified 111 haplotypes (H) (Figure 20) with differential basal CHO
levels (Figure 21). About 75% of
these haplotypes in the AD population have a frequency below 1%, 10% have a
frequency between 1% and 2%, 8% have a frequency between 2% and 5%, and only 4%
of the haplotypes are present in more than 5% of AD patients (Fig. 20). The
haplotypes most frequently found are H55 (33-CT-CC-AG-CC)(8.79%), H58
(33-CT-CC-GG-CC) and H37 (33-CC-CC-AG-CC) (7.07%). Haplotypes H104
(44-CC-CC-AA-CC)(0.11%), H110 (44-TT-CC-AG-CG)(0.11%) and H98 (34-TT-CC-AA-CG) (0.11%)
showed the highest CHO levels, and the lowest levels corresponded to haplotypes
H26 (23-TT-CG-AG-CC) (0.11%), H8 (23-CC-CG-AG-CC)(0.21%), H50
(33-CC-GG-AG-CC)(0.21%), and H63 (33-CT-CG-AA-GG)(0.11%) (Figure 21).
Basal CHO levels tend to be higher in AD patients as compared to GP
levels (Figure 22-23). APOE-related
blood total CHO profiles are qualitatively distinct among carriers of different
APOE genotypes (Figure 24). The results of APOE-related cholesterol response to
hypolipemic treatment in hypercholesterolemic AD patients revealed that in
absolute terms all APOE variants
respond similarly (RR>70%) to treatment with a significant reductionin CHO levels
(p<0.001) (Figure 25-26);
however, genotype-related correlation analysis case-by-case (Figure 27) and comparative correlation
analyses of APOE variants (Figure 28) show a clear differential APOE-related pattern of CHO response to
treatment.
Carriers of APOB-C/C, APOB-C/T and APOB-T/T
variants exhibit a similar response (RR>80%), with a significant decrease in
CHO levels after treatment (Figure. 29) and almost identical efficiency
in comparative analyses (Figure. 30). APOC3-C/C, APOC3-C/G and APOC3-G/G carriers also respond
similarly (p<0.001) (RR>80%) (Figure. 31), with a differential
comparative profile (Figure 32). CETP-A/A,
CETP-A/G and CETP-G/G carriers
show an identical response (p<0.001; RR>80%) (Figure 33), with
insignificant variability in comparative studies (Figure 34). The same
therapeutic response is observed in LPL-C/C, LPL-C/G and LPL-G/G
carriers (p<0.001; RR>80%) (Figure 35), though in this case LPL-C/C are the best responders, LPL-C/G are intermediate responders, and
LPL-G/G are the most heterogeneous
responders (Figure 36).
CYP haplotype-related blood total CHO levels
are very heterogeneous (Figure 37), but absolute values of total CHO
among the most frequent haplotypes are almost identical (Figure 38). The
histograms of frequency associated with CHO levels are qualitatively different
among carriers of different CYP variants (Figure 39-40). Basal CHO
levels are higher in AD patients harboring the CYP2D6-*1/*1 (p<0.05) and *1xN/*1
genotypes (p<0.003) than in the corresponding GP genotypes (Figure 41),
but no differences have been found according to their EM, IM, PM or UM
condition (Figure 42). The therapeutic response according to SNPs of
metabolic genes (CYP2D6, CYP2C9, CYP2C19,
CYP3A4/4) in hypercholesterolemic patients is variable and geno-phenotype-dependent.
Although all CYP2D6 variants exhibit a positive response to treatment,
significant differences have only been detected in 2D6-*1/*1 (p<0.001), 2D6-*1/*4
(p<0.001) and 2D6-*1/*6 carriers
(p<0.05) (Figure 43). In absolute values, CYP2D6 extensive (EM),
intermediate (IM), poor (PM) and ultra-rapid (UM) metabolizers behave in a
similar manner with a significant reduction in CHO levels (p<0.001) (Figure
44); however, the RR is different in EMs (81%), IMs (78%), PMs (84%), and
UMs (90%) (Figure 44), indicating a variable efficiency of CYP2D6
enzymes (Figure 45-46). The comparative analysis indicates that carriers
of mutant enzymes (PMs>UMs), with limitations in drug metabolism, display a
more efficient response to hypolipemic treatment (Figure 45,46).
No differences are present in basal CHO
levels between the GP and AD patients (Figure 47,48). CYP2C9-EMs, IMs
and PMs (Figure 49) show a similar response (p<0.001), with lower RR
(75%) in PMs as compared with EMs (81%) and IMs (82%), and a clear differential
comparative profile (Figure 50).
AD cases harboring the CYP2C19-*1/*2 genotype (Figure 51), corresponding to
CYP2C19-IMs (Figure 52), exhibit higher basal CHO levels (p<0.05)
than their homologous in the GP (Figure 51,52).
The CHO response among CYP2C19-EMs, IMs, PMs
and UMs is more variable, with PMs showing a deficient response (RR=84%) in
comparison to EMs (p<0.001; RR=81%), IMs (p<0.001; RR=78%), and UMs
(p<0.001; RR=90%), and a clearly different behavioral profile, especially in
PMs and UMs (Figure 53-55).
CYP3A4/5
geno-phenotypes in AD and GP show similar basal CHO levels (Figure 56).
CYP3A4/5-RMs respond poorly to hypolipemic treatment, with the worst RR (66%),
whereas CYP3A4/5-EMs and IMs exhibit an excellent response (p<0.001;
RR>80%) (Figure 57,58).
Most of these effects can, in part, be explained on a pharmacogenetic
basis. It is obvious that a simple stratification of patients according to
single genotypes is of poor value for a fine interpretation of pharmacogenetic
results; however, the integration of gene clusters associated with specific
phenotypes yields informative haplotypes with potential utility in
pharmacogenetic studies. It is likely that thousands of genes are involved in
CHO metabolism, and probably not a single gene plays an absolute dominant role over
the others; however, some genes exert a powerful effect on other congeners
associated with a specific pathogenic cascade (e.g. APOE in AD) or a pharmacogenetic pathway (e.g. APOE vs. CYPs in AD
treatment with donepezil) [3,6,17,33,66,67]. Several pathogenic (ACE, APOA1, APOA5, APOB, APOC3, APOE, CETP,
FGB, GNB3, LIPC, MMP3, MTTP, NOS3, PON) and mechanistic genes (ABCB1, ABCC1, APOA1, APOA5, APOB, APOC3,
APOE, CRP, CYP11B2, HMGCR, IL10,
IL6, LDLR, MMP3, PON1, TNF) are potentially influenced by atorvastatin. This statin is a major
substrate of CYP2C8 and CYP3A4/5; it is a strong inhibitor of CYP2C19, a
moderate inhibitor of ABCB1, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4
and HMGCR, and an inducer of CYP2B6 and CYP7A1. Atorvastatin is transported by
ABCA1, ABCB1, ABCB11, ABCC1, ABCC2, ABCC3, ABCG2, SLCO1B1 and SLCO1B3 proteins,
and interacts with the products of various pleiotropic genes (APOA1, APOE, CRP, CYP11B2, ESR1, GNB3,
HTR3B, IL6, IL10, ITGB3, MMP3, TNF, USP5) [38] (Table 2). The lipid-lowering effects and the anti-atherosclerotic
properties of LipoEsar are APOE-dependent,
with APOE-3 carriers acting as the
best responders and APOE-4 carriers
behaving as the worst responders [5,6]. Sex-related changes in CHO response to
statins have been reported in carriers of the HMGCR-AA genotype at rs3846662, who have higher levels of total and
LDL-CHO. The percentage reduction in LDL-CHO upon statin treatment is decreased
in women with the AA genotype compared with women without it. In
hypercholesterolemic patients, HMGCR
alternative splicing may explain 22-55% of the variance in statin response [139].
The powerful effect of Atorvastatin in CYP3A4/5-IMs is the result of a poor
metabolization of Atorvastatin by mutant CYP3A4/5 enzymes, since Atorvastatin
is a major substrate of CYP3A4/5. In contrast, the lack of effect in
CYP3A4/5-RMs results from a rapid destruction of the drug in the liver mediated
by excessive CYP3A4/5 enzymatic activity. Therefore, the dose of statins should
be adjusted to the metabolizing condition of each patient to optimize the
lipid-lowering effects of statins and to avoid toxicity [38]. Furthermore, the
co-administration of the nutraceutical LipoEsar enhances the hypolipemic effect
of Atorvastatin and facilitates a dose reduction of the statin by 50%,
minimizing potential ADRs in susceptible patients.
PHARMACOEPIGENOMICS
Pharmacogenetics alone does not predict all phenotypic variation in
drug response [27]. The genes involved in the pharmacogenomic network are under
the regulatory control of the epigenetic machinery (DNA methylation, histone
modifications, miRNA regulation), this configuring the novel pharmacoepigenomic
apparatus [27]. Epigenetics involves heritable alterations of gene expression,
chromatin organization, and microRNA (miRNA) regulation without changes in DNA
sequence. Classical epigenetic mechanisms, including DNA methylation and
histone modifications, and regulation by microRNAs (miRNAs), are among the
major regulatory elements that control metabolic pathways at the molecular
level, with epigenetic modifications regulating gene expression
transcriptionally and miRNAs suppressing gene expression post-transcriptionally
[140]. Methylation varies spatially across the genome with a majority of the
methylated sites mapping to intragenic regions [141]. About 70% of CpG
dinucleotides within the human genome are methylated. Not only nuclear DNA
(nDNA), but also mitochondrial DNA (mtDNA) may be subjected to epigenetic
modifications related to disease development, environmental exposure, drug
treatment and aging.
Several pathogenic genes (Table
3) and many other AD-related susceptibility genes with direct or indirect
influence on the AD phenotype (i.e. genes associated with vascular risk factors
and lipid metabolism)(Table 4)
contain methylated CpG sites which exhibit alterations in DNA methylation
[142,143]. Different modalities of histone aberrations are present in AD
[27-29,142,144,145]. Alterations in epigenetically-regulated miRNAs may
contribute to the abnormal expression of pathogenic genes in AD [146,147].
Several lncRNAs are dysregulated in AD (Sox2OT, 1810014B01Rik, BC200, BACE1-AS,
NAT-Rad18, 17A, GDNFOS) [147]. Examples of miRNAs directly linked to AD
pathogenesis include miR-34a (1p36.22), miR-34b/c (11q23.1), miR-107
(10q23.31), miR-124 (8p23.1/8p12.3/20q13.33), miR-125b (11q24.1/21q21.1), and
miR-137 (1p21.3); and examples of epigenetically-regulated miRNAs with targets
linked to AD pathogenesis are let-7b (22q13.1), miR-9 (1q22/5q14.3/15q26.1),
miR-132/212 (17p13.3), miR-146a (5q34), miR-148a (7p15.2), miR-184 (15q25.1),
and miR-200 (miR-200b/200a/429, 1p36.33; miR-200c/141, 12p13.31) [146].
AD-related SNPs interfere with miRNA gene regulation and affect AD
susceptibility. The significant interactions include target SNPs present in
seven genes related to AD prognosis with the miRNAs- miR-214, -23a & -23b,
-486-3p, -30e*, -143, -128, -27a &-27b, -324-5p and -422a. The dysregulated
miRNA network contributes to the aberrant gene expression in AD [148-150].
Epigenetic regulation is also responsible for the tissue-specific
expression of genes involved in pharmacogenetic processes, and epigenetics
plays a key role in the development of drug efficacy, safety and resistance.
Epigenetic changes affect CYP expression, major transporter function, and
nuclear receptor interactions [151-154]. Variable methylation patterns have
been detected in genes encoding phase I-III enzymes (Table 5). Although this is a still poorly explored field,
epigenetic regulation of genes encoding drug-metabolizing enzymes (CYP1A1, 1A2, 1B1, 1A6, 2A13, 2B6, 2C8, 2C9,
2C18, 2C19, 2D6, 2E1, 2J2, 2F1, 2R1, 2S1, 2W1, 3A4, 3A5, 3A7, 3A43, UGT1, GSTP1),
drug transporters (ABCB1/MDR1/P-gp,
ABCC1/MRP1, ABCC11/MRP8, ABCG2/BCRP, SLC19A1, SLC22A8), and nuclear
receptors (RARB2, ESR1, NR1I2, HNF41)
has been documented in pioneering studies of pharmacoepigenetics [27,151-154].
Epigenetic modifications are also associated with drug resistance
[27,153,155]. The acquisition of drug resistance is tightly regulated by
post-transcriptional regulators such as RNA-binding proteins (RBPs) and miRNAs,
which change the stability and translation of mRNA-encoding factors involved in
cell survival, proliferation, epithelial-mesenchymal transition, and drug
metabolism [153]. In the complex cascade of pharmacoepigenetic events, the
epigenetic factory may act as a promiscuous, redundant security system in which
several miRNAs target genes encoding epigenetic regulators. For example,
miR-29, -29c, -370, and -450A target DNMT3A, and miR-29, -148, and -29b target
DNMT3B, inducing hypomethylation and expression of tumor suppressor genes;
let-7a, miR-26a, -101, -138, and -124 target EZH2, decreasing histone
methylation and increasing expression of tumor suppressor genes; miR-449 and
-874 target HDAC1, inducing growth arrest by decreasing histone acetylation;
miR-1 and -155 target HDAC4, promoting myogenesis and impairing transcriptional
activity of B-cell lymphoma 6 (BCL6); miR-627 and -155 target JMJD1A,
decreasing histone demethylation and hypoxic gene expression; miR-132 and
-483-5p target MECP2, promoting demethylation and cell differentiation [156].
Furthermore, epigenetic drugs reverse epigenetic changes in gene expression and
might open new avenues in AD therapeutics [29,30,145,157].
CONCLUSIONS
1. AD is a complex
disorder with a tetravalent phenotype (neuropathological, neurobehavioral,
age-related, and gender-related components).
2. Major determinants
of therapeutic outcome in AD include age- and sex-related factors, pathogenic
phenotype, concomitant disorders, treatment modality and polypharmacy, and
pharmacogenetics.
3. Different
categories of genes are potentially involved in the pharmacogenetic network
responsible for drug efficacy and safety.
4. Pathogenic,
mechanistic, metabolic, transporter, and pleiotropic genes represent the major
genetic determinants of response to treatment in AD.
5. The genes involved
in the pharmacogenomic network are under the regulatory control of the
epigenetic machinery (DNA methylation, histone modifications, miRNA
regulation), this configuring the novel pharmacoepigenomic apparatus and
constituting a novel source of potential therapeutic targets.
6. By-products of
these genes are integrated in transcriptomic, proteomic and metabolic networks
which are disrupted in AD and represent potential targets for therapeutic
intervention.
7. In pharmacogenetic
studies with conventional anti-dementia drugs and combination treatments, APOE-4 carriers are the worst responders
and APOE-3 carriers are the best
responders; patients harboring a large (L) number of poly T repeats in intron 6
of the TOMM40 gene (L/L or S/L
genotypes) in haplotypes associated with APOE-4
are the worst responders to treatment; patients with short (S) TOMM40 poly T variants (S/S genotype) in
haplotypes with APOE-3 are the best
responders to treatment; and CYP2D6
and ABCB1 variants may influence the
therapeutic response to conventional treatments.
8. Over 80% of AD
patients are daily consumers of different treatments for concomitant disorders.
Only 20% of the Caucasian population are extensive metabolizers for the
tetragenic haplotype integrated by CYP2D6,
CYP2C9, CYP2C19 and CYP3A4/5 variants.
9. Tetragenic
haplotypes integrating CYP2D6, CYP2C9,
CYP2C19 and CYP3A4/5 variants
yield 156 genotypes. The most frequent haplotype is H3
(1/1-1/1-1/1-3/3)(20.87%), representing full extensive metabolizers, and only
17 haplotypes exhibit a frequency higher than 1% in the Spanish population.
10. AD patients exhibit
at least 111 pentagenic (APOE-APOB-APOC3-CETP-LPL)
haplotypes associated with cholesterol levels. The highest levels of cholesterol
are present in carriers of the haplotype H104 (44-CC-CC-AA-CC) and the lowest
levels of cholesterol are detected in carriers of the haplotype H26
(23-TT-CG-AG-CC).
11. The response of
cholesterol to specific hypolipemic treatments in hypercholesterolemic AD
patients is highly efficient in over 70% of the cases and associates with APOE variants, CHO-related haplotypes
and drug-specific CYP metabolizer geno-phenotypes.
12. The implementation of pharmacogenomic
protocols is essential to prescribe more accurately, avoid adverse reactions
and optimize the limited therapeutic resources available for the treatment of
dementia.
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