Genome-wide association analysis identifies common variants associated with measures of disease progression in patients with Alzheimer's disease

Newhouse, Stephen, Proitsi, Petroula, Sattlecker, Martina, Lunnon, Katie, Ibrahim, Zina, Johnston, Caroline, Lourdusamy, Anbarasu, Lupton, Michelle, Powell, John, Khondoker, Mizanur ORCID: https://orcid.org/0000-0002-1801-1635, Soininen, Hilkka, Kloszewska, Iwona, Mecocci, Patrizia, Tsolaki, Magda, Vellas, Bruno, Lovestone, Simon, Hodges, Angela and Dobson, Richard (2012) Genome-wide association analysis identifies common variants associated with measures of disease progression in patients with Alzheimer's disease. In: Alzheimer's Association International Conference 2012, 2012-07-14 - 2012-07-19.

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Abstract

Background: Alzheimer's disease (AD), a leading cause of dementia among the elderly, is a complex neurodegenerative disorder with a strong genetic component. Recent genome-wide association studies (GWAS) have identified loci that alter the risk of AD, but little is known about the genetic risk factors involved with rate of cognitive decline (ROD). Here we report on one of the first GWAS with disease progression in AD patients from the EU funded AddNeuroMed (ANM) project. Methods: Alzheimer's patients provided MMSE, CDR and ADAS-cog scores at baseline and for four additional visits over the subsequent year. Rates of decline were calculated over this period using mixed models and the slopes were used as quantitative traits for association analysis. The models included significant covariates such as education and medication. We imputed ∼37 million SNPs from the 1000 Genomes reference panel b37, June 2011 release into the ANM samples using IMPUTEv2. After stringent quality control, 5, 561, 292 SNPs remained for association analysis with ADAS-cog, CDR and MMSE. All analyses were performed under an additive model adjusting for age, sex and APOE4 status using SNPTESTv2 . We corrected for population stratification using principle component analysis (Genomic inflation factors for ADAS-cog, CDR and MMSE were 1.00, 1.02 and 1.01 respectively). Results: We identified 21 novel signals with p<5x10-8: 13 with ADAS-cog, two with CDR and six with MMSE. We also observed nominal association (P <0.05, min-P = 5x10-6) with multiple variants in and around ( ± 250kb) many of the previously identified GWAS AD loci and candidate genes: CLU, ABCA7, CR1, PICALM, CD33, MS4A6A, MS4A4E, BIN1, CD2AP, EXOC3L2, TNF, SORL1, FTO, ACE, MTHFD1L and ATXN1, and with the recently identified GWAS hits for ROD in subjects with mild cognitive impairment (MCI): ACOT11, MYO9A and UBR5. Conclusions: We have identified new loci associated with ROD in AD patients and provide further evidence for known AD/MCI candidate loci with ROD. We will report results of a meta-analysis with the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.

Item Type:	Conference or Workshop Item (Other)
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Epidemiology and Public Health Faculty of Medicine and Health Sciences > Research Groups > Public Health and Health Services Research (former - to 2023) Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Centres > Population Health
Depositing User:	Pure Connector
Date Deposited:	24 Sep 2016 01:08
Last Modified:	19 Oct 2023 04:00
URI:	https://ueaeprints.uea.ac.uk/id/eprint/60564
DOI:	10.1016/j.jalz.2012.05.253

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