Previous genome-wide association studies have identified dozens of susceptibility loci for sporadic Alzheimer's disease, but few of these loci have been validated in longitudinal cohorts. Establishing predictive models of Alzheimer's disease based on these novel variants is clinically important for verifying whether they have pathological functions and provide a useful tool for screening of disease risk. In the current study, we performed a two-stage genome-wide association study of 3913 patients with Alzheimer's disease and 7593 controls and identified four novel variants (rs3777215, rs6859823, rs234434, and rs2255835; P-combined = 3.07x10(-19), 2.49x10(-23), 1.35x10(-67), and 4.81x10(-9), respectively) as well as nine variants in the apolipoprotein E region with genome-wide significance (P<5.0x10(-8)). Literature mining suggested that these novel single nucleotide polymorphisms are related to amyloid precursor protein transport and metabolism, antioxidation, and neurogenesis. Based on their possible roles in the development of Alzheimer's disease, we used different combinations of these variants and the apolipoprotein E status and successively built 11 predictive models. The predictive models include relatively few single nucleotide polymorphisms useful for clinical practice, in which the maximum number was 13 and the minimum was only four. These predictive models were all significant and their peak of area under the curve reached 0.73 both in the first and second stages. Finally, these models were validated using a separate longitudinal cohort of 5474 individuals. The results showed that individuals carrying risk variants included in the models had a shorter latency and higher incidence of Alzheimer's disease, suggesting that our models can predict Alzheimer's disease onset in a population with genetic susceptibility. The effectiveness of the models for predicting Alzheimer's disease onset confirmed the contributions of these identified variants to disease pathogenesis. In conclusion, this is the first study to validate genome-wide association study-based predictive models for evaluating the risk of Alzheimer's disease onset in a large Chinese population. The clinical application of these models will be beneficial for individuals harbouring these risk variants, and particularly for young individuals seeking genetic consultation.
基金:
Key Project of the National Natural Science Foundation of China [81530036]; National Key Scientific Instrument and Equipment Development Project [31627803]; Mission Program of Beijing Municipal Administration of Hospitals [SML20150801]; Beijing Scholars Program; Beijing Brain Initiative from Beijing Municipal Science & Technology Commission [Z201100005520016, Z201100005520017, Z161100000216137]; Project for Outstanding Doctor with Combined Ability of Western and Chinese Medicine; Beijing Municipal Commission of Health and Family Planning [PXM2019_026283_000003]
第一作者单位:[1]Capital Med Univ, Xuanwu Hosp, Natl Clin Res Ctr Geriatr Dis, Innovat Ctr Neurol Disorders, Changchun St 45, Beijing 100053, Peoples R China[2]Capital Med Univ, Xuanwu Hosp, Natl Clin Res Ctr Geriatr Dis, Dept Neurol, Changchun St 45, Beijing 100053, Peoples R China
通讯作者:
通讯机构:[1]Capital Med Univ, Xuanwu Hosp, Natl Clin Res Ctr Geriatr Dis, Innovat Ctr Neurol Disorders, Changchun St 45, Beijing 100053, Peoples R China[2]Capital Med Univ, Xuanwu Hosp, Natl Clin Res Ctr Geriatr Dis, Dept Neurol, Changchun St 45, Beijing 100053, Peoples R China[23]Capital Med Univ, Xuanwu Hosp, Dept Radiol, Beijing, Peoples R China[24]Capital Med Univ, Xuanwu Hosp, Dept Nucl Med, Beijing, Peoples R China[25]Beijing Key Lab Geriatr Cognit Disorders, Beijing, Peoples R China[26]Capital Med Univ, Clin Ctr Neurodegenerat Dis & Memory Impairment, Beijing, Peoples R China[27]Beijing Inst Brain Disorders, Ctr Alzheimers Dis, Beijing, Peoples R China[*1]Capital Med Univ, Xuanwu Hosp, Dept Nucl Med, Dept Radiol, Changchun St 45, Beijing 100053, Peoples R China
推荐引用方式(GB/T 7714):
Jia Longfei,Li Fangyu,Wei Cuibai,et al.Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study[J].BRAIN.2021,144(3):924-937.doi:10.1093/brain/awaa364.
APA:
Jia, Longfei,Li, Fangyu,Wei, Cuibai,Zhu, Min,Qu, Qiumin...&Jia, Jianping.(2021).Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study.BRAIN,144,(3)
MLA:
Jia, Longfei,et al."Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study".BRAIN 144..3(2021):924-937