Genetic report abstractInfluence of Alzheimer's disease genes on cognitive decline: the Guangzhou Biobank Cohort Study
Introduction
Clinical dementia is becoming more prevalent because of changing demographics, particularly in developing countries like China with a rapidly aging population (Ferri et al., 2005). For those subjects with a clinical diagnosis of dementia in Hong Kong, Alzheimer's disease (AD) was the most common likely cause (73.5%), whereas 22.4% had vascular dementia, and 3.9% had dementia with symptoms of Parkinson's disease (Lam et al., 2008). AD usually begins with subtle and poorly recognized failure of memory and slowly becomes more severe and eventually incapacitating.
Generally reflected by increasing difficulties with memory or speed of information processing, cognitive decline deterioration in cognitive function is usually associated with aging. The appearance of significant cognitive decline predicts the progression to mild cognitive impairment and then dementia (including AD), if not already at one of these stages (Cherbuin et al., 2009, Dik et al., 2000). Because cognitive decline is often a prodromal symptom of AD, understanding of AD would uncover potential reasons for cognitive decline or vice versa (Daviglus et al., 2010).
Though twin studies showed cognition performance or cognitive decline is highly heritable (Lee et al., 2010), even the APOE locus is not consistently associated with cognitive decline across different samples or populations (Devore et al., 2009, Dik et al., 2000, Lee et al., 2003). Therefore, more genes are expected to be found to explain the phenotypic variance of this complex trait, although this will require very large studies. Genetic risk factors from genome wide association studies (GWAS) as well as large systematic reviews for AD can serve to select candidate genes for cognitive decline (Bertram et al., 2007, Sleegers et al., 2010). Genetic variants from CLU, CR1, PICALM, and BIN1 genes have been repeatedly reported to be associated with AD (Bertram et al., 2008, Harold et al., 2009, Hu et al., 2011b, Kamboh et al., 2012, Lambert et al., 2009), and some of them are reported to be also involved in the trajectories of cognitive function (Sweet et al., 2012). These newly found AD genes are clustered in biological pathways (amyloid pathway, lipid metabolism pathway, chaperone, and chronic inflammatory pathway) which play an important role in the development of late-onset AD (Sleegers et al., 2010) and probably also in disease progression from cognitive decline. Most studies investigating the effect of AD genes on cognitive decline or performance have been conducted in Caucasian populations (Barral et al., 2012, Hu et al., 2011a, Sweet et al., 2012); therefore, there is a need to evaluate AD genes for cognitive decline in Asian subjects.
Initiated in 2003, the Guangzhou Biobank Cohort Study (GBCS) has recruited more than 30,000 southern Chinese older people and collected multidimensional data, including demographic, epidemiologic, and biochemical variables, with both an initial and follow-up assessment separated by around 3 years (Jiang et al., 2006). Several cross-sectional studies have been done for cognitive measurement and environmental factors (Au Yeung et al., 2010, Heys et al., 2010, Xu et al., 2011). Here, we aimed to examine the impact of 30 known genetic risk variants (within 29 genes) for AD on cognitive decline. Meanwhile, potential genetic risk factors were co-investigated with risk factors (sex, age, education level, and neurologic disease status) previously demonstrated to be associated with decline (Xu et al., 2014) to evaluate their independent effects and genetic by environment interactions.
Section snippets
Participants
The subjects in GBCS were recruited from a community social and welfare association, the Guangzhou Health and Happiness Association for the Respectable Elders, which has more than 110,000 members accounting for more than 7% of Guangzhou's permanent residents aged 50 years or older (Jiang et al., 2006). Data on demographic and socioeconomic characteristics, lifestyle factors, occupational exposure, cognitive function, and disease history were collected from standardized interviews at both
Results
Table 1 shows the basic characteristics of DWRT, putative confounders, and genotyping rate in the complete cohort and genotyped subjects (separately for cognitive decline cases and control subjects). In the complete cohort sample, increasing age, male, and lower education were significantly associated with decreasing DWRT scores, with p < 2 × 10−16. In the genotyped sample, the means of score change (−3.7 vs. 0.1) and baseline age (62.4 vs. 65.4) were far different between cognitive decline
Discussion
In this study, we investigated the effects of known AD-related genetic risk variants on cognitive decline using subjects from the GBCS. Unlike some previous studies of normal cognition to mild cognitive disorder or impairment (Cherbuin et al., 2009, Song et al., 2012), we used a reliable and valid measure of cognitive decline (Ferri et al., 2005) on a large population-based cohort with longitudinal data. We found APOE ε4 homozygotes and ACE rs1800764C carriers (especially for subjects with
Disclosure statement
The authors declare that they have no competing interests.
Acknowledgements
This study was supported by Hong Kong Research Grants Council General Research Fund (HKU 7623/09M), Hong Kong Health and Health Services Research Fund (06070981), the Key Medical and Health Foundation of Guangzhou (201102A211004), and the Bureau of Guangzhou Science and Technology (2013J4100031).
The Guangzhou Biobank Cohort Study (GBCS) investigators include: the Guangzhou No. 12 Hospital: WS Zhang, M Cao, T Zhu, B Liu, CQ Jiang (Co-PI); The University of Hong Kong: CM Schooling, SM McGhee, GM
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