Apolipoprotein genotype for prediction of Alzheimer's disease in older Japanese: the Hisayama Study

Plasma biomarkers for predicting the development of dementia in a community-dwelling older Japanese population

AIM

To assess the association between plasma amyloid β (Aβ) 42/40, phosphorylated tau (p-τ)181, glial fibrillary acidic protein (GFAP), or neurofilament light chain (NfL) and the risk of dementia and to determine whether these plasma biomarkers could improve the ability to predict incident dementia in a general older population.

METHODS

A total of 1346 Japanese community-dwelling individuals aged ≥65 years without dementia were followed prospectively for 5.0 years. Plasma biomarkers were quantified using a Simoa HD-X analyzer. A Cox proportional hazards model was used to estimate the hazard ratios of each plasma biomarker level for the risk of dementia.

RESULTS

During the follow-up, 151 participants developed dementia, of whom 108 had Alzheimer disease (AD) and 43 non-Alzheimer dementia (non-AD). Lower plasma Aβ42/40 levels and higher plasma p-τ181 levels were significantly associated with developing AD but not non-AD, whereas significant associations were observed between higher plasma levels of GFAP and NfL and risk of both AD and non-AD (all P for trend <0.05). In addition, adding these four plasma biomarkers into a model consisting of the total score of the dementia risk model significantly improved the predictive ability for incident dementia.

CONCLUSION

Our findings suggest that plasma Aβ42/40 and p-τ181 are specific markers of AD, and plasma GFAP and NfL are potential biomarkers for all-cause dementia in the general Japanese older population. In addition, the measurement of these plasma biomarkers may be a useful and relatively low-invasive procedure for identifying individuals at high risk for developing dementia in clinical practice.

External validation of existing dementia prediction models on observational health data

BACKGROUND

Many dementia prediction models have been developed, but only few have been externally validated, which hinders clinical uptake and may pose a risk if models are applied to actual patients regardless. Externally validating an existing prediction model is a difficult task, where we mostly rely on the completeness of model reporting in a published article. In this study, we aim to externally validate existing dementia prediction models. To that end, we define model reporting criteria, review published studies, and externally validate three well reported models using routinely collected health data from administrative claims and electronic health records.

METHODS

We identified dementia prediction models that were developed between 2011 and 2020 and assessed if they could be externally validated given a set of model criteria. In addition, we externally validated three of these models (Walters' Dementia Risk Score, Mehta's RxDx-Dementia Risk Index, and Nori's ADRD dementia prediction model) on a network of six observational health databases from the United States, United Kingdom, Germany and the Netherlands, including the original development databases of the models.

RESULTS

We reviewed 59 dementia prediction models. All models reported the prediction method, development database, and target and outcome definitions. Less frequently reported by these 59 prediction models were predictor definitions (52 models) including the time window in which a predictor is assessed (21 models), predictor coefficients (20 models), and the time-at-risk (42 models). The validation of the model by Walters (development c-statistic: 0.84) showed moderate transportability (0.67-0.76 c-statistic). The Mehta model (development c-statistic: 0.81) transported well to some of the external databases (0.69-0.79 c-statistic). The Nori model (development AUROC: 0.69) transported well (0.62-0.68 AUROC) but performed modestly overall. Recalibration showed improvements for the Walters and Nori models, while recalibration could not be assessed for the Mehta model due to unreported baseline hazard.

CONCLUSION

We observed that reporting is mostly insufficient to fully externally validate published dementia prediction models, and therefore, it is uncertain how well these models would work in other clinical settings. We emphasize the importance of following established guidelines for reporting clinical prediction models. We recommend that reporting should be more explicit and have external validation in mind if the model is meant to be applied in different settings.

Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease

Alzheimer’s disease (AD) is one of the most complicated progressive neurodegenerative brain disorders, affecting millions of people around the world. Ageing remains one of the strongest risk factors associated with the disease and the increasing trend of the ageing population globally has significantly increased the pressure on healthcare systems worldwide. The pathogenesis of AD is being extensively investigated, yet several unknown key components remain. Therefore, we aimed to extract new knowledge from existing data. Ten gene expression datasets from different brain regions including the hippocampus, cerebellum, entorhinal, frontal and temporal cortices of 820 AD cases and 626 healthy controls were analyzed using the robust rank aggregation (RRA) method. Our results returned 1713 robust differentially expressed genes (DEGs) between five brain regions of AD cases and healthy controls. Subsequent analysis revealed pathways that were altered in each brain region, of which the GABAergic synapse pathway and the retrograde endocannabinoid signaling pathway were shared between all AD affected brain regions except the cerebellum, which is relatively less sensitive to the effects of AD. Furthermore, we obtained common robust DEGs between these two pathways and predicted three miRNAs as potential candidates targeting these genes; hsa-mir-17-5p, hsa-mir-106a-5p and hsa-mir-373-3p. Three transcription factors (TFs) were also identified as the potential upstream regulators of the robust DEGs; ELK-1, GATA1 and GATA2. Our results provide the foundation for further research investigating the role of these pathways in AD pathogenesis, and potential application of these miRNAs and TFs as therapeutic and diagnostic targets.

Study design and baseline characteristics of a population-based prospective cohort study of dementia in Japan: the Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD)

BACKGROUND

The burden of dementia is growing rapidly and has become a medical and social problem in Japan. Prospective cohort studies have been considered an effective methodology to clarify the risk factors and the etiology of dementia. We aimed to perform a large-scale dementia cohort study to elucidate environmental and genetic risk factors for dementia, as well as their interaction.

METHODS

The Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) is a multisite, population-based prospective cohort study of dementia, which was designed to enroll approximately 10,000 community-dwelling residents aged 65 years or older from 8 sites in Japan and to follow them up prospectively for at least 5 years. Baseline exposure data, including lifestyles, medical information, diets, physical activities, blood pressure, cognitive function, blood test, brain magnetic resonance imaging (MRI), and DNA samples, were collected with a pre-specified protocol and standardized measurement methods. The primary outcome was the development of dementia and its subtypes. The diagnosis of dementia was adjudicated by an endpoint adjudication committee using standard criteria and clinical information according to the Diagnostic and Statistical Manual of Mental Disorders, 3rd Revised Edition. For brain MRI, three-dimensional acquisition of T1-weighted images was performed. Individual participant data were pooled for data analyses.

RESULTS

The baseline survey was conducted from 2016 to 2018. The follow-up surveys are ongoing. A total of 11,410 individuals aged 65 years or older participated in the study. The mean age was 74.4 years, and 41.9% were male. The prevalence of dementia at baseline was 8.5% in overall participants. However, it was 16.4% among three sites where additional home visit and/or nursing home visit surveys were performed. Approximately two-thirds of dementia cases at baseline were Alzheimer's disease.

CONCLUSIONS

The prospective cohort data from the JPSC-AD will provide valuable insights regarding the risk factors and etiology of dementia as well as for the development of predictive models and diagnostic markers for the future onset of dementia. The findings of this study will improve our understanding of dementia and provide helpful information to establish effective preventive strategies for dementia in Japan.

Cross-disease analysis of Alzheimer's disease and type-2 Diabetes highlights the role of autophagy in the pathophysiology of two highly comorbid diseases

Evidence is accumulating that the main chronic diseases of aging Alzheimer's disease (AD) and type-2 diabetes mellitus (T2DM) share common pathophysiological mechanisms. This study aimed at applying systems biology approaches to increase the knowledge of the shared molecular pathways underpinnings of AD and T2DM. We analysed transcriptomic data of post-mortem AD and T2DM human brains to obtain disease signatures of AD and T2DM and combined them with protein-protein interaction information to construct two disease-specific networks. The overlapping AD/T2DM network proteins were then used to extract the most representative Gene Ontology biological process terms. The expression of genes identified as relevant was studied in two AD models, 3xTg-AD and ApoE3/ApoE4 targeted replacement mice. The present transcriptomic data analysis revealed a principal role for autophagy in the molecular basis of both AD and T2DM. Our experimental validation in mouse AD models confirmed the role of autophagy-related genes. Among modulated genes, Cyclin-Dependent Kinase Inhibitor 1B, Autophagy Related 16-Like 2, and insulin were highlighted. In conclusion, the present investigation revealed autophagy as the central dys-regulated pathway in highly co-morbid diseases such as AD and T2DM allowing the identification of specific genes potentially involved in disease pathophysiology which could become novel targets for therapeutic intervention.

Population-based dementia prediction model using Korean public health examination data: A cohort study

The early identification and prevention of dementia is important for reducing its worldwide burden and increasing individuals’ quality of life. Although several dementia prediction models have been developed, there remains a need for a practical and precise model targeted to middle-aged and Asian populations. Here, we used national Korean health examination data from adults (331,126 individuals, 40–69 years of age, mean age: 52 years) from 2002–2003 to predict the incidence of dementia after 10 years. We divided the dataset into two cohorts to develop and validate of our prediction model. Cox proportional hazards models were used to construct dementia prediction models for the total group and sex-specific subgroups. Receiver operating characteristics curves, C-statistics, calibration plots, and cumulative hazards were used to validate model performance. Discriminative accuracy as measured by C-statistics was 0.81 in the total group (95% confidence interval (CI) = 0.81 to 0.82), 0.81 in the male subgroup (CI = 0.80 to 0.82), and 0.81 in the female subgroup (CI = 0.80 to 0.82). Significant risk factors for dementia in the total group were age; female sex; underweight; current hypertension; comorbid psychiatric or neurological disorder; past medical history of cardiovascular disease, diabetes mellitus, or hypertension; current smoking; and no exercise. All identified risk factors were statistically significant in the sex-specific subgroups except for low body weight and current hypertension in the female subgroup. These results suggest that public health examination data can be effectively used to predict dementia and facilitate the early identification of dementia within a middle-aged Asian population.

Prevalence of and risk factors for cerebral microbleeds in a general Japanese elderly community

Background

We investigated the prevalence of and risk factors for cerebral microbleeds (CMBs) in a cross-sectional study of a general population of Japanese elderly.

Methods

In 2012, brain MRI scanning at 1.5T and comprehensive health examination were conducted for 1281 residents aged 65 years or older. CMBs were defined as ovoid hypointensity lesions less than 10 mm in diameter on T2*-weighted images and classified into deep/infratentorial or lobar CMBs. Age- and sex-specific and overall prevalence of CMBs were estimated, and the associations of traditional cardiovascular risk factors and APOE polymorphism with the presence of CMBs were examined using a logistic regression analysis.

Results

The crude prevalences of total, deep/infratentorial, and lobar CMBs were 18.7% (n = 240), 13.5% (n = 173), and 9.6% (n = 123), respectively. The prevalence of total CMBs was 23.0% in men and 15.5% in women and increased with aging in both sexes (both p for trend <0.01). Hypertension was significantly associated with the presence of both deep/infratentorial and lobar CMBs. Lower serum total cholesterol was a significant risk factor for deep/infratentorial CMBs, but not for lobar CMBs, while APOE ε4 carriers had a significantly higher likelihood only of lobar CMBs compared with noncarriers.

Conclusions

Our study suggests that approximately 1 of 5 Japanese elderly people have CMBs, and that risk factors for deep/infratentorial and lobar CMBs are different, indicating the distinct pathologic backgrounds of these lesions.

Epidemiology, associated burden, and current clinical practice for the diagnosis and management of Alzheimer's disease in Japan

The burden of dementia in Japan is large and growing. With the world’s fastest aging population, it is estimated that one in five elderly people will be living with dementia in Japan by 2025. The most common form of dementia is Alzheimer’s disease (AD), accounting for around two-thirds of dementia cases. A systematic review was conducted to examine the epidemiology and associated burden of AD in Japan and to identify how AD is diagnosed and managed in Japan. English and Japanese language databases were searched for articles published between January 2000 and November 2015. Relevant Japanese sources, clinical practice guideline registers, and reference lists were also searched. Systematic reviews and cohort and case–control studies were eligible for inclusion, with a total of 60 studies included. The most recent national survey conducted in six regions of Japan reported the mean prevalence of dementia in people aged ≥65 years to be 15.75% (95% CI: 12.4, 22.2%), which is much higher than the previous estimated rate of 10% in 2010. AD was confirmed as the predominant type of dementia, accounting for 65.8% of all cases. Advancing age and low education were the most consistently reported risk factors for AD dementia. Japanese guidelines for the management of dementia were released in 2010 providing specific guidance for AD about clinical signs, image findings, biochemical markers, and treatment approaches. Pharmacotherapies and non-pharmacotherapies to relieve cognitive symptoms were introduced, as were recommendations to achieve better patient care. No studies reporting treatment patterns were identified. Due to population aging and growing awareness of AD in Japan, health care expenditure and associated burden are expected to soar. This review highlights the importance of early detection, diagnosis, and treatment of AD as strategies to minimize the impact of AD on society in Japan.

Evaluation of a Genetic Risk Score to Improve Risk Prediction for Alzheimer's Disease

Effective prevention of Alzheimer's disease (AD) requires the development of risk prediction tools permitting preclinical intervention. We constructed a genetic risk score (GRS) comprising common genetic variants associated with AD, evaluated its association with incident AD and assessed its capacity to improve risk prediction over traditional models based on age, sex, education, and APOEɛ4. In eight prospective cohorts included in the International Genomics of Alzheimer's Project (IGAP), we derived weighted sum of risk alleles from the 19 top SNPs reported by the IGAP GWAS in participants aged 65 and older without prevalent dementia. Hazard ratios (HR) of incident AD were estimated in Cox models. Improvement in risk prediction was measured by the difference in C-index (Δ-C), the integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI>0). Overall, 19,687 participants at risk were included, of whom 2,782 developed AD. The GRS was associated with a 17% increase in AD risk (pooled HR = 1.17; 95% CI =   [1.13-1.21] per standard deviation increase in GRS; p-value =  2.86×10-16). This association was stronger among persons with at least one APOEɛ4 allele (HRGRS = 1.24; 95% CI =   [1.15-1.34]) than in others (HRGRS = 1.13; 95% CI =   [1.08-1.18]; pinteraction = 3.45×10-2). Risk prediction after seven years of follow-up showed a small improvement when adding the GRS to age, sex, APOEɛ4, and education (Δ-Cindex =  0.0043 [0.0019-0.0067]). Similar patterns were observed for IDI and NRI>0. In conclusion, a risk score incorporating common genetic variation outside the APOEɛ4 locus improved AD risk prediction and may facilitate risk stratification for prevention trials.

Association of Alzheimer's Disease With APOE and IL-1α Gene Polymorphisms

Apolipoprotein E (ApoE) gene polymorphisms are thought to be the most important genetic risk factor in the pathogenesis of late onset and sporadic Alzheimer's disease (AD). Moreover, interleukin-1α (IL-1α) is found to be associated with the pathogenesis of AD. In this research, ∊2, ∊3, and ∊4 polymorphisms of ApoE gene and C889T polymorphism of IL-1α gene were genotyped in patients with AD and controls. Genotyping was performed by real-time polymerase chain reaction. ∊3/∊3 and ∊3/∊4 genotype frequencies were significantly higher in control and case groups, respectively. While ∊3 allele frequencies were significantly higher in the control group, ∊2 and ∊4 allele frequencies were significantly higher among the cases with AD. No difference was found between the groups according to C889T polymorphism of IL-1α. In conclusion, we demonstrated that there was a strong association between ApoE ∊4 allele and AD, while there was no relation with IL-1α C889T polymorphisms for this study.

Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review

BACKGROUND

Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. To evaluate these models we undertook a systematic review in 2010 and updated this in 2014 due to the increase in research published in this area. Here we include a critique of the variables selected for inclusion and an assessment of model prognostic performance.

METHODS

Our previous systematic review was updated with a search from January 2009 to March 2014 in electronic databases (MEDLINE, Embase, Scopus, Web of Science). Articles examining risk of dementia in non-demented individuals and including measures of sensitivity, specificity or the area under the curve (AUC) or c-statistic were included.

FINDINGS

In total, 1,234 articles were identified from the search; 21 articles met inclusion criteria. New developments in dementia risk prediction include the testing of non-APOE genes, use of non-traditional dementia risk factors, incorporation of diet, physical function and ethnicity, and model development in specific subgroups of the population including individuals with diabetes and those with different educational levels. Four models have been externally validated. Three studies considered time or cost implications of computing the model.

INTERPRETATION

There is no one model that is recommended for dementia risk prediction in population-based settings. Further, it is unlikely that one model will fit all. Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score. Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction, before applying the particular models in population or clinical settings.

Usefulness of data from magnetic resonance imaging to improve prediction of dementia: population based cohort study

OBJECTIVE

To determine whether the addition of data derived from magnetic resonance imaging (MRI) of the brain to a model incorporating conventional risk variables improves prediction of dementia over 10 years of follow-up.

DESIGN

Population based cohort study of individuals aged ≥ 65.

SETTING

The Dijon magnetic resonance imaging study cohort from the Three-City Study, France.

PARTICIPANTS

1721 people without dementia who underwent an MRI scan at baseline and with known dementia status over 10 years' follow-up.

MAIN OUTCOME MEASURE

Incident dementia (all cause and Alzheimer's disease).

RESULTS

During 10 years of follow-up, there were 119 confirmed cases of dementia, 84 of which were Alzheimer's disease. The conventional risk model incorporated age, sex, education, cognition, physical function, lifestyle (smoking, alcohol use), health (cardiovascular disease, diabetes, systolic blood pressure), and the apolipoprotein genotype (C statistic for discrimination performance was 0.77, 95% confidence interval 0.71 to 0.82). No significant differences were observed in the discrimination performance of the conventional risk model compared with models incorporating data from MRI including white matter lesion volume (C statistic 0.77, 95% confidence interval 0.72 to 0.82; P=0.48 for difference of C statistics), brain volume (0.77, 0.72 to 0.82; P=0.60), hippocampal volume (0.79, 0.74 to 0.84; P=0.07), or all three variables combined (0.79, 0.75 to 0.84; P=0.05). Inclusion of hippocampal volume or all three MRI variables combined in the conventional model did, however, lead to significant improvement in reclassification measured by using the integrated discrimination improvement index (P=0.03 and P=0.04) and showed increased net benefit in decision curve analysis. Similar results were observed when the outcome was restricted to Alzheimer's disease.

CONCLUSIONS

Data from MRI do not significantly improve discrimination performance in prediction of all cause dementia beyond a model incorporating demographic, cognitive, health, lifestyle, physical function, and genetic data. There were, however, statistical improvements in reclassification, prognostic separation, and some evidence of clinical utility.

Opportunities in pharmacogenomics for the treatment of Alzheimer's disease

ABSTRACT 

In Alzheimer's disease (AD), approximately 10–20% of direct costs are associated with pharmacological treatment. Pharmacogenomics account for 30–90% variability in pharmacokinetics and pharmacodynamics. Genes potentially involved in the pharmacogenomics outcome include pathogenic, mechanistic, metabolic, transporter and pleiotropic genes. Over 75% of the Caucasian population is defective for the CYP2D6+2C9+2C19 cluster. Polymorphic variants in the APOE-TOMM40 region influence AD pharmacogenomics. APOE-4 carriers are the worst responders and APOE-3 carriers are the best responders to conventional treatments. TOMM40 poly T-S/S carriers are the best responders, VL/VL and S/VL carriers are intermediate responders and L/L carriers are the worst responders. The 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.

Incidence rates of dementia, Alzheimer disease, and vascular dementia in the Japanese American population in Seattle, WA: the Kame Project

There are few studies on the incidence of dementia in representative minority populations in the United States; however, no population-based study has been conducted on Japanese American women. We identified 3045 individuals aged 65+ with at least 1 parent of Japanese descent living in King County, WA in the period 1992 to 1994, of whom 1836 were dementia-free and were examined every 2 years (1994 to 2001) to identify incident cases of all dementias, Alzheimer disease (AD), vascular dementia (VaD), and other dementias. Cox regression was used to examine associations with age, sex, years of education, and apolipoprotein (APOE)-ε4. Among 173 incident cases of dementia, the overall rate was 14.4/1000/y, with rates being slightly higher among women (15.9/1000) than men (12.5/1000). Rates roughly doubled every 5 years for dementia and AD; the age trend for VaD and other dementias was less consistent. Sex was not significantly related to incidence of dementia or its subtypes in adjusted models. There was a trend for an inverse association with increasing years of education. APOE-ε4 was a strong risk factor for all dementias [hazard ratio (HR)=2.89; 95% confidence interval (CI), 1.88-4.46], AD (HR=3.27; 95% CI, 2.03-5.28), and VaD (HR=3.33; 95% CI, 1.34-8.27). This study is the first to report population-based incidence rates for both Japanese American men and women.

APOE ε4 and the risk for Alzheimer disease and cognitive decline in African Americans and Yoruba

BACKGROUND

There is little information on the association of the APOEe4 allele and AD risk in African populations. In previous analyses from the Indianapolis-Ibadan dementia project, we have reported that APOE ε4 increased the risk for Alzheimer's disease (AD) in African Americans but not in Yoruba. This study represents a replication of this earlier work using enriched cohorts and extending the analysis to include cognitive decline.

METHODS

In this longitudinal study of two community dwelling cohorts of elderly Yoruba and African Americans, APOE genotyping was conducted from blood samples taken on or before 2001 (1,871 African Americans & 2,200 Yoruba). Mean follow up time was 8.5 years for African Americans and 8.8 years for Yoruba. The effects of heterozygosity or homozygosity of ε4 and of the possession of e4 on time to incident AD and on cognitive decline were determined using Cox's proportional hazards regression and mixed effects models.

RESULTS

After adjusting for covariates, one or two copies of the APOE ε4 allele were significant risk factors for incident AD (p < 0.0001) and cognitive decline in the African-American population (p < 0001). In the Yoruba, only homozygosity for APOE ε4 was a significant risk factor for AD (p = 0.0002) but not for cognitive decline (p = 0.2346), however, possession of an e4 allele was significant for both incident AD (p = 0.0489) and cognitive decline (p = 0.0425).

CONCLUSIONS

In this large longitudinal comparative study, APOE ε4 had a significant, but weaker, effect on incident AD and on cognitive decline in Yoruba than in African Americans. The reasons for these differences remain unclear.

Pharmacogenomics of Alzheimer's disease: novel therapeutic strategies for drug development

Alzheimer's disease (AD) is a major problem of health and disability, with a relevant economic impact on our society. Despite important advances in pathogenesis, diagnosis, and treatment, its primary causes still remain elusive, accurate biomarkers are not well characterized, and the available pharmacological treatments are not cost-effective. As a complex disorder, AD is a polygenic and multifactorial clinical entity in which hundreds of defective genes distributed across the human genome may contribute to its pathogenesis. Diverse environmental factors, cerebrovascular dysfunction, and epigenetic phenomena, together with structural and functional genomic dysfunctions, lead to amyloid deposition, neurofibrillary tangle formation, and premature neuronal death, the major neuropathological hallmarks of AD. Future perspectives for the global management of AD predict that genomics and proteomics may help in the search for reliable biomarkers. In practical terms, the therapeutic response to conventional drugs (cholinesterase inhibitors, multifactorial strategies) is genotype-specific. Genomic factors potentially involved in AD pharmacogenomics include at least five categories of gene clusters: (1) genes associated with disease pathogenesis; (2) genes associated with the mechanism of action of drugs; (3) genes associated with drug metabolism (phase I and II reactions); (4) genes associated with drug transporters; and (5) pleiotropic genes involved in multifaceted cascades and metabolic reactions. The implementation of pharmacogenomic strategies will contribute to optimize drug development and therapeutics in AD and related disorders.

Personalized Medicine of Alzheimer’s Disease

Alzheimer’s disease (AD) is a major problem of health and disability, with a relevant economic impact on society (e.g., €177 billion in Europe). Despite important advances in pathogenesis, diagnosis, and treatment, The primary causes of AD remain elusive, accurate biomarkers are not well characterized, and available pharmacological treatments are not cost-effective. As a complex disorder, AD is polygenic and multifactorial: hundreds of defective genes distributed across the human genome may contribute to its pathogenesis (with the participation of diverse environmental factors, cerebrovascular dysfunction, and epigenetic phenomena) and lead to amyloid deposition, neurofibrillary tangle formation, and premature neuronal death. Future perspectives for the global management of AD predict that structural and functional genomics and proteomics may help in the search for reliable biomarkers, and that pharmacogenomics may be an option in optimizing drug development and therapeutics.

Altered expression of diabetes-related genes in Alzheimer's disease brains: the Hisayama study

Diabetes mellitus (DM) is considered to be a risk factor for dementia including Alzheimer's disease (AD). However, the molecular mechanism underlying this risk is not well understood. We examined gene expression profiles in postmortem human brains donated for the Hisayama study. Three-way analysis of variance of microarray data from frontal cortex, temporal cortex, and hippocampus was performed with the presence/absence of AD and vascular dementia, and sex, as factors. Comparative analyses of expression changes in the brains of AD patients and a mouse model of AD were also performed. Relevant changes in gene expression identified by microarray analysis were validated by quantitative real-time reverse-transcription polymerase chain reaction and western blotting. The hippocampi of AD brains showed the most significant alteration in gene expression profile. Genes involved in noninsulin-dependent DM and obesity were significantly altered in both AD brains and the AD mouse model, as were genes related to psychiatric disorders and AD. The alterations in the expression profiles of DM-related genes in AD brains were independent of peripheral DM-related abnormalities. These results indicate that altered expression of genes related to DM in AD brains is a result of AD pathology, which may thereby be exacerbated by peripheral insulin resistance or DM.