Brain tissue microarrays in dementia research: white matter microvascular pathology in Alzheimer's disease

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Tissue Microarray Lipidomic Imaging Mass Spectrometry Method: Application to the Study of Alcohol-Related White Matter Neurodegeneration

Central nervous system (CNS) white matter pathologies accompany many diseases across the lifespan, yet their biochemical bases, mechanisms, and consequences have remained poorly understood due to the complexity of myelin lipid-based research. However, recent advances in matrix-assisted laser desorption/ionization-imaging mass spectrometry (MALDI-IMS) have minimized or eliminated many technical challenges that previously limited progress in CNS disease-based lipidomic research. MALDI-IMS can be used for lipid identification, semi-quantification, and the refined interpretation of histopathology. The present work illustrates the use of tissue micro-arrays (TMAs) for MALDI-IMS analysis of frontal lobe white matter biochemical lipidomic pathology in an experimental rat model of chronic ethanol feeding. The use of TMAs combines workload efficiency with the robustness and uniformity of data acquisition. The methods described for generating TMAs enable simultaneous comparisons of lipid profiles across multiple samples under identical conditions. With the methods described, we demonstrate significant reductions in phosphatidylinositol and increases in phosphatidylcholine in the frontal white matter of chronic ethanol-fed rats. Together with the use of a novel rapid peak alignment protocol, this approach facilitates reliable inter- and intra-group comparisons of MALDI-IMS data from experimental models and could be extended to human disease states, including using archival specimens.

Preparation, construction and high-throughput automated analysis of human brain tissue microarrays for neurodegenerative disease drug development

A major challenge in the treatment of neurodegenerative disorders is the translation of effective therapies from the lab to the clinic. One approach to improve this process is the use of human brain tissue microarray (HBTMA) technology to aid in the discovery and validation of drug targets for brain disorders. In this protocol we describe a platform for the production of high-quality HBTMAs that can be used for drug target discovery and validation. We provide examples of the use of this platform and describe detailed protocols for HBTMA design, construction and use for both protein and mRNA detection. This platform requires less tissue and reagents than single-slide approaches, greatly increasing throughput and capacity, enabling samples to be compared in a more consistent way. It takes 4 d to construct a 60 core HBTMA. Immunohistochemistry and in situ hybridization take a further 2 d. Imaging of each HBTMA slide takes 15 min, with subsequent high-content analysis taking 30 min-2 h.

Tissue microarray (TMA) use in post mortem neuropathology

BACKGROUND

Tissue microarrays (TMAs), where each block (and thus section) contains multiple tissue cores from multiple blocks potentially allow more efficient use of tissue, reagents and time in neuropathology.

NEW METHOD

The relationship between data from TMA cores and whole sections was investigated using 'virtual' TMA cores. This involved quantitative assessments of microglial pathology in white matter lesions and motor neuron disease, alongside qualitative TDP-43 inclusion status in motor neuron disease cases. Following this, a protocol was developed for TMA construction.

RESULTS

For microglial pathology we found good concordance between virtual cores and whole sections for volume density using one 1.75 mm core (equivalent to a 2 mm core after accounting for peripheral tissue loss). More sophisticated microglial cell size and measures required two cores. Qualitative results of pTDP-43 pathology showed use of one 1.75 mm core gave a 100 % sensitivity and specificity within grey matter, and 88.3 % sensitivity and 100 % specificity within white matter. A method of producing the TMAs was suitable for immunohistochemistry both manually and by autostainer, with the minimal core loss from the microscope slide.

COMPARISON WITH EXISTING METHODS

TMAs have been used infrequently in post mortem neuropathology research. However, we believe TMAs give comparable tissue assessment results and can be constructed, sectioned and stained with relative ease.

CONCLUSIONS

We found TMAs could be used to assess both quantitative (microglial pathology) and qualitative pathology (TDP-43 proteinopathy) with greatly reduced quantities of tissue, time and reagents. These could be used for further work to improve data acquisition efficiency.

The Full Spectrum of Alzheimer's Disease Is Rooted in Metabolic Derangements That Drive Type 3 Diabetes

The standard practice in neuropathology is to diagnose Alzheimer's disease (AD) based on the distribution and abundance of neurofibrillary tangles and Aβ deposits. However, other significant abnormalities including neuroinflammation, gliosis, white matter degeneration, non-Aβ microvascular disease, and insulin-related metabolic dysfunction require further study to understand how they could be targeted to more effectively remediate AD. This review addresses non-Aβ and non-pTau AD-associated pathologies, highlighting their major features, roles in neurodegeneration, and etiopathic links to deficits in brain insulin and insulin-like growth factor signaling and cognitive impairment. The discussion delineates why AD with its most characteristic clinical and pathological phenotypic profiles should be regarded as a brain form of diabetes, i.e., type 3 diabetes, and entertains the hypothesis that type 3 diabetes is just one of the categories of insulin resistance diseases that can occur independently or overlap with one or more of the others, including type 2 diabetes, metabolic syndrome, and nonalcoholic fatty liver disease.

Quantitative neuropathology: an update on automated methodologies and implications for large scale cohorts

A tissue microarray (TMA) has previously been developed for use in assessment of neurodegenerative diseases. We investigated the variation of pathology loads in semi-quantitative score categories and how pathology load related to disease progression. Post-mortem tissue from 146 cases were used; Alzheimer's disease (AD) (n = 36), Lewy body disease (LBD) (n = 56), mixed AD/dementia with Lewy bodies (n = 14) and controls (n = 40). TMA blocks (one per case) were constructed using tissue cores from 15 brain regions including cortical and subcortical regions. TMA tissue sections were stained for hyperphosphorylated tau (HP-_T), β amyloid and α-synuclein (αsyn), and quantified using an automated image analysis system. Cases classified as Braak stage VI displayed a wide variation in HP-_T pathology in the entorhinal cortex (interquartile range 4.13-44.03%). The interquartile range for β amyloid in frontal cortex in cases classified as Thal phase 5 was 6.75-17.03% and for αsyn in the cingulate in cases classified as McKeith neocortical LBD was 0.04-0.58%. In AD and control cases, HP-_T load predicted the Braak stage (p < 0.001), β amyloid load predicted Thal phase (p < 0.001) and αsyn load in LBD cases predicted McKeith type of LBD (p < 0.001). Quantitative data from TMA assessment highlight the range in pathological load across cases classified with 'severe' pathology and is beneficial to further elucidate the heterogeneity of neurodegenerative diseases. Quantifying pathology in multiple brain regions may allow identification of novel clinico-pathological phenotypes for the improvement of intra vitam stratification of clinical cohorts according to underlying pathologies.

The role of neuropathological markers in the interpretation of neuropsychiatric disorders: Focus on fetal and perinatal programming

The study of neuropathological markers in patients affected by mental/psychiatric disorders is relevant for the comprehension of the pathogenesis and the correlation with the clinical symptomatology. The neuropathology of Alzheimer's disease (AD) recognizes intraneuronal and extracellular neurofibrillary formation responsible for neuronal degeneration. Immunohistochemical studies discovered many interesting results for a better interpretation of the AD pathogenesis, while the "metal hypothesis" supports that metal ions might differentially influence the formation of amyloid aggregates. The most relevant pathological findings reported in schizophrenia originate from computer assisted tomography (CT), Magnetic Resonance Imaging (MRI) studies and Diffusion Tensor Imaging (DTI), suggesting the brain abnormalities involved in the pathophysiology of schizophrenia. The theory of fetal programming illustrates the epigenetic factors that may act during the intrauterine life on brain development, with relevant consequences on the susceptibility to develop AD or schizophrenia later in life. The neuropathological interpretation of AD and schizophrenia shows that the presence of severe neuropathological changes is not always associated with severe cognitive impairment. A better dialogue between psychiatrics and pathologists might help to halt insurgence and progression of neurodegenerative diseases.

Assessing fibrinogen extravasation into Alzheimer's disease brain using high-content screening of brain tissue microarrays

BACKGROUND

Tissue microarrays are commonly used to evaluate disease pathology however methods to automate and quantify pathological changes are limited.

NEW METHOD

This article demonstrates the utility of the VSlide scanner (MetaSystems) for automated image acquisition from immunolabelled tissue microarray slides, and subsequent automated image analysis with MetaXpress (Molecular Devices) software to obtain objective, efficient and reproducible data from immunolabelled tissue microarray sections.

RESULTS

Significant increases in fibrinogen immunolabelling were observed in 29 Alzheimer's disease cases compared to 28 control cases analysed from a single tissue microarray slide. Western blot analysis also demonstrated significant increases in fibrinogen immunolabelling in 6 Alzheimer's cases compared to 6 control cases. The observed changes were also validated with gold standard blinded manual H-scoring.

COMPARISON WITH EXISTING METHOD

VSlide Metafer software offers a 'tissue microarray acquisition' plugin for easy mapping of tissue cores with their original position on the tissue microarray map. High resolution VSlide images are compatible with MetaXpress image analysis software. This article details the coupling of these two technologies to accurately and reproducibly analyse immunolabelled tissue microarrays within minutes, compared to the gold standard method of manual counting using H-scores which is significantly slower and prone to inter-observer variation.

CONCLUSIONS

Here, we couple brain tissue microarray technology with high-content screening and automated image analysis as a powerful way to address bottle necks in data generation and improve throughput, as well as sensitivity to study biological/pathological changes in brain disease.

Tissue microarrays: fast-tracking protein expression at the cellular level

Tissue microarrays maximize returns in cellular pathology whilst minimizing the use of cells and tissues. They are made by arraying cores of tissue taken from multiple donor blocks into a single recipient block. Accordingly, the histology and pathology of several hundred tissues can be represented in one tissue microarray that, when stained by immunohistochemistry, provides comprehensive topographic information on protein expression. Used with complimentary techniques, such as complementary DNA microarray analysis, tissue microarrays are providing valuable data for the identification of new markers of disease and assisting in the discovery of therapeutic targets. They are also leading a revolution in cellular pathology as high-throughput technology is introduced to maximize the information provided.

White matter atrophy in Alzheimer's disease variants

BACKGROUND

In comparison with late-onset Alzheimer's disease (LOAD, onset, >65 years), early-age-of-onset Alzheimer's disease (EOAD, onset, <65 years) more often presents with language, visuospatial, and/or executive impairment, often occurring earlier than a progressive memory deficit. The logopenic variant of primary progressive aphasia (lv-PPA) and posterior cortical atrophy (PCA) have recently been described as possible atypical variants of EOAD. Lv-PPA is characterized by isolated language deficit, whereas PCA is characterized by predominant visuospatial deficits. Severe hemispheric gray matter (GM) atrophy associated with EOAD, lv-PPA, and PCA has been described, but regional patterns of white matter (WM) damage are still poorly understood.

METHODS

Using structural magnetic resonance imaging and voxel-based morphometry, we investigated WM damage in patients with EOAD (n = 16), PCA (n = 13), lv-PPA (n = 10), and LOAD (n = 14) at presentation and 72 age-matched control subjects.

RESULTS

In patients with EOAD, PCA, and lv-PPA, WM atrophy was centered on the lateral temporal and parietal regions, including the cingulum and posterior corpus callosum. Compared with control subjects, patients with lv-PPA showed more severe left parietal damage, and patients with PCA showed more severe occipital atrophy. Moreover, patients with EOAD had greater cingulum atrophy compared with those with LOAD. LOAD showed WM damage in the medial temporal regions and less extensive hemispheric involvement.

CONCLUSION

Patterns of WM damage in EOAD, lv-PPA, and PCA are consistent with the clinical syndromes and GM atrophy patterns. WM injury in AD atypical variants may contribute to symptoms and disease pathogenesis.

Brain networks in posterior cortical atrophy: a single case tractography study and literature review

Posterior cortical atrophy (PCA) is rare neurodegenerative dementia, clinically characterized by a progressive decline in higher-visual object and space processing. After a brief review of the literature on the neuroimaging in PCA, here we present a study of the brain structural connectivity in a patient with PCA and progressive isolated visual and visuo-motor signs. Clinical and cognitive data were acquired in a 58-years-old patient (woman, right-handed, disease duration 18 months). Brain structural and diffusion tensor (DT) magnetic resonance imaging (MRI) were obtained. A voxel-based morphometry (VBM) study was performed to explore the pattern of gray matter (GM) atrophy, and a fully automatic segmentation was assessed to obtain the hippocampal volumes. DT MRI-based tractography was used to assess the integrity of long-range white matter (WM) pathways in the patient and in six sex- and age-matched healthy subjects. This PCA patient had a clinical syndrome characterized by left visual neglect, optic ataxia, and left limb apraxia, as well as mild visuo-spatial episodic memory impairment. VBM study showed bilateral posterior GM atrophy with right predominance; DT MRI tractography demonstrated WM damage to the right hemisphere only, including the superior and inferior longitudinal fasciculi and the inferior fronto-occipital fasciculus, as compared to age-matched controls. The homologous left-hemisphere tracts were spared. No difference was found between left and right hippocampal volumes. These data suggest that selective visuo-spatial deficits typical of PCA might not result from cortical damage alone, but by a right-lateralized network-level dysfunction including WM damage along the major visual pathways.

Extending the tissue microarray data exchange specification for inclusion of data analysis results

Background:

The Tissue Microarray Data Exchange Specification (TMA DES) is an eXtensible Markup Language (XML) specification for encoding TMA experiment data in a machine-readable format that is also human readable. TMA DES defines Common Data Elements (CDEs) that form a basic vocabulary for describing TMA data. TMA data are routinely subjected to univariate and multivariate statistical analysis to determine differences or similarities between pathologically distinct groups of tumors for one or more markers or between markers for different groups. Such statistical analysis tests include the t-test, ANOVA, Chi-square, Mann-Whitney U, and Kruskal-Wallis tests. All these generate output that needs to be recorded and stored with TMA data.

Materials and Methods:

We propose extending the TMA DES to include syntactic and semantic definitions of CDEs for describing the results of statistical analyses performed upon TMA DES data. These CDEs are described in this paper and it is illustrated how they can be added to the TMA DES. We created a Document Type Definition (DTD) file defining the syntax for these CDEs, and a set of ISO 11179 entries providing semantic definitions for them. We describe how we wrote a program in R that read TMA DES data from an XML file, performed statistical analyses on that data, and created a new XML file containing both the original XML data and CDEs representing the results of our analyses. This XML file was submitted to XML parsers in order to confirm that they conformed to the syntax defined in our extended DTD file. TMA DES XML files with deliberately introduced errors were also parsed in order to verify that our new DTD file could perform error checking. Finally, we also validated an existing TMA DES XML file against our DTD file in order to demonstrate the backward compatibility of our DTD.

Results:

Our experiments demonstrated the encoding of analysis results using our proposed CDEs. We used XML parsers to confirm that these XML data were syntactically correct and conformed to the rules specified in our extended TMA DES DTD. We also demonstrated that this extended DTD was capable of being used to successfully perform error checking, and was backward compatible with pre-existing TMA DES data which did not use our new CDEs.

Conclusions:

The TMA DES allows Tissue Microarray data to be shared. A variety of statistical tests are used to analyze such data. We have proposed a set of CDEs as an extension to the TMA DES which can be used to annotate TMA DES data with the results of statistical analyses performed on that data. We performed experiments which demonstrated the usage of TMA DES data containing our proposed CDEs.

Alzheimer's disease (AD) and executive dysfunction. A case-control study on the significance of frontal white matter changes detected by diffusion tensor imaging (DTI)

White matter (WM) changes are frequently seen on structural imaging in AD but the clinical relevance of these changes is uncertain. Frontal WM pathology is often observed upon neuropathological examination in AD. Since frontal cortical/sub-cortical pathology is known to relate to executive dysfunction, the aim was to elucidate if frontal WM changes in AD correlated with executive dysfunction. In all, 15 AD patients and 15 age-matched control cases were investigated in the study, which covered conventional magnetic resonance imaging (MRI), DTI, neuropsychiatric and neuropsychological examinations. Reduced performance on neuropsychological testing of executive function correlated significantly with an increasing degree of frontal WM changes detected by DTI in the AD group, while no such correlation was observed for the controls. Conventional semi-quantitative MRI assessment did not correlate with results on neuropsychological testing of executive function in any of the groups. The structural correlate to certain dimensions of executive dysfunction in AD patients could be related to changes in the deep frontal WM. DTI appears to be more sensitive in the detection of clinically significant WM alterations than conventional semi-quantitative MRI.

The adult human brain in preclinical drug development

Neurodegenerative disorders are caused by the death and dysfunction of brain cells, but despite a huge worldwide effort, no neuroprotective treatments that slow cell death currently exist. The failure of translation from animal models to humans in the clinic is due to many factors including species differences, human brain complexity, age, patient variability and disease-specific phenotypes. Additional methods are therefore required to overcome these obstacles in neuroprotective drug development. Incorporating target validation using human brain-tissue microarray screening and direct human brain-cell testing at an early preclinical stage to isolate molecules that protect the human brain may be an effective strategy.

Human postmortem brain tissue and 2-mm tissue microarrays

The authors constructed tissue microarray (TMA) blocks from human postmortem brain including numerous core samples measuring 2 mm in diameter from various anatomic regions. These TMA sections were then processed using various stainings and pretreatment techniques to evaluate their properties. The loss of core samples ranged from 2% to 100% and was significantly influenced by the type of glass slide used; it was lowest (2-8%) with SuperFrost Plus slides. The losses were not significantly altered when applying the most demanding pretreatment procedures or using human brain tissue with a long postmortem delay. A slight influence on the quality and the repeatability of some of the IHC stainings was seen by the postmortem delay, by the brain region, or by the glass slide used. One special feature of the constructed brain TMA block including many anatomic brain regions is that persons who lack skills in neuroanatomy can identify various brain structures simply by following the x-y coordinates. Thus, the applications of this brain TMA block in neurologic research by scientists with different skill bases remain to be determined.

Human brain tissue microarrays as a platform to investigate diseases of the nervous system

We constructed tissue microarray (TMA) blocks containing post-mortem human brain tissue from subjects with clinically and neuropathologically verified Alzheimer's disease (AD), corticobasal degeneration (CBD), progressive supranuclear palsy, Lewy body disease, multisystem atrophy (MSA) as well as an age matched control. Fifteen donor blocks were merged into two TMA blocks containing 72, 2-mm punch core samples with representative brain regions generally affected in degenerative disorders. Hyperphosphorylated-gamma, alpha-synuclein and beta-amyloid-related pathologies were estimated. The diseases were easily recognized by evaluating the two TMA sections and the results assessing TMA sections were comparable with the assessment of the whole brain sections. The assessment of TMA sections revealed concomitant multifocal alpha-synuclein pathology in AD, mild tau-involvement in the case of MSA and a slight AD-type pathology in the case of CBD. These findings emphasize the importance of searching for a variety of pathologies in "the whole brain" rather than restricting the examination to a few vulnerable regions. Furthermore, the TMA methodology clearly reduced the number of sections needed for evaluating the whole brain, it increased the amount of research material generated and furthermore no detailed neuroanatomical knowledge was required for assessment of data.

White matter mapping in Alzheimer's disease: A neuropathological study

White matter disease (WMD) with pervasive non-focal subtotal tissue loss is frequently seen in Alzheimer's disease (AD) upon neuropathological examination. Although WMD has varying effects on AD symptoms, accurate clinical detection is difficult due partly to scarcity of correlative structural imaging and histopathological studies. Neuropathological studies of WMD severity and distribution have been conducted earlier using semi-quantitative methods. A technique for quantifying WMD objectively in large white matter areas, based on optical density (OD) measurements on images of scanned whole-brain sections, was developed and was validated using conventional microscopic assessment. Altogether, 16 AD cases with concomitant WMD (AD-WMD) and 9 cases of AD without WMD (AD-only) were analysed. The OD values correlated significantly with the neuropathological severity of WMD and were significantly lower in AD-WMD than in AD-only in frontal, frontoparietal, temporal and parietal white matter but not in the occipital white matter, the frontal OD difference being greatest. Useful baseline information on WMD distribution in AD to relate to in vivo imaging results was obtained.

Decreasing myelin density reflected increasing white matter pathology in Alzheimer's disease--a neuropathological study

BACKGROUND

White matter disease (WMD) is frequently seen in Alzheimer's disease (AD) at neuropathological examination. It is defined as a subtotal tissue loss with a reduction of myelin, axons and oligodendrocytes as well as astrocytosis. Studies quantitatively defining the myelin loss in AD are scarce. The aim was to develop a method that could provide numerical values of myelin density in AD. The purpose was to compare the myelin contents in increasing grades of pathology of WMD, with age and cortical AD pathology as well as in different regions of the brain in AD.

MATERIAL AND METHODS

Sixteen cases with AD and concomitant WMD were investigated with an in-house developed image analysis technique to determine the myelin attenuation with optical density (OD) in frontoparietal, parietal, temporal and occipital white matter on whole brain coronal sections stained for myelin with Luxol Fast Blue (LFB). The OD values in LFB were compared grouped according to Haematoxylin/Eosin (HE) evaluated mild, moderate and severe WMD or normal tissue. The OD values were also correlated with age and cortical AD pathology and compared between the different studied white matter regions.

RESULTS

Increasing severity of WMD was associated with a statistically significant OD reduction. No correlation was seen between age and OD or overall cortical AD pathology. The OD values were significantly lower in frontoparietal-compared to occipital white matter.

CONCLUSIONS

Myelin loss in AD with WMD is a marked morphologic component of the disease and it is possible to determine the reduction objectively in neuropathological specimens with quantitative measures. This may be of use for clinical diagnostics including brain imaging.

Genomic characterization of Alzheimer’s disease and genotype-related phenotypic analysis of biological markers in dementia

More than 180 genes distributed across the human genome are potentially involved in the pathogenesis of Alzheimer’s disease (AD). The AD population shows a higher genetic variation rate than the control population. Significant differences in allelic distribution and frequency exist when AD-related polygenic clusters are compared with other forms of dementia, indicating that the genetic component in neurodegenerative dementia differs from that of other CNS disorders. The characterization of AD genotype-related phenotypic profiles reveals substantial differences in biological markers among AD clusters associated with different genes and/or allelic combinations. AD and dementia with vascular component (DVC) are the most prevalent forms of dementia. Both clinical entities share many similarities, but they differ in their major phenotypic and genotypic profiles, as revealed by structural and functional genomics studies. Comparative phenotypic studies have identified significant differences in 25% of more than 100 parametric variables, including anthropometric values, cardiovascular function, blood pressure, lipid metabolism, uric acid metabolism, peripheral calcium homeostasis, liver function, alkaline phosphatase, lactate dehydrogenase, red and white blood cells, regional brain atrophy, and brain blood flow velocity. Functional genomic studies incorporating apolipoprotein E (APOE)-related changes in biological markers extended the difference between AD and DVC by up to 57%. Structural genomic studies with AD-related genes, including APP, MAPT, APOE, PS1, PS2, A2M, ACE, AGT, cFOS, and PRNP, demonstrate different genetic profiles in AD and DVC, with an absolute genetic variation rate in the range of 30–80%, depending upon genes and genetic clusters. The relative polymorphic variation in genetic clusters integrated by two, three or four genes associated with AD ranges from 1 to 3%. The main phenotypic differences in AD are genotype dependent, indicating a powerful influence of polygenic factors on the AD phenotypic profile. All these genotypic and phenotypic variations bring about important consequences for the pharmacogenomics of AD.