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Cited by 67Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchGenetic Associations and Epidemiology

Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study

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Jia, Longfei, Li, Fangyu, Wei, Cuibai, Zhu, Min, Qu, Qiumin, Qin, Wei, Tang, Yi, Shen, Luxi +36 more·2021·Brain
DOI 10.1093/brain/awaa364PMC PMC8041344
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Abstract

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; Pcombined = 3.07 × 10−19, 2.49 × 10−23, 1.35 × 10−67, and 4.81 × 10−9, respectively) as well as nine variants in the apolipoprotein E region with genome-wide significance (P < 5.0 × 10−8). 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.

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  • Jia et al. identified 34 candidate SNPs that were validated in a replication cohort.

    “Jia et al. analyzed 1595 AD patients and 2474 healthy subjects, and identified 34 candidate SNPs [29], that were validated in a replication cohort of 2234 AD patients and 7319 healthy subjects.”

    From Genetics of Alzheimer’s disease: An East Asian perspective (2023) · cites this paper as [29]

    The Results section ('Results from genome-wide association studies'; page unavailable) says 34 candidate SNPs were selected for testing in an independent Chinese cohort, but only 13 passed the replication significance threshold. It reports 1,679 patients and 2,508 controls in the first stage, and 2,234 patients and 5,085 controls in the second—not the control counts in the citing sentence. (LLM, conf=0.92)

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Authors
Jia, L., Li, F., Wei, C., Zhu, M., Qu, Q., Qin, W., Tang, Y., Shen, L., Wang, Y., Shen, L., Li, H., Peng, D., Tan, L., Luo, B., Guo, Q., Tang, M., Du, Y., Zhang, J., Zhang, J., Lyu, J., Li, Y., Zhou, A., Wang, F., Chu, C., Song, H., Wu, L., Zuo, X., Han, Y., Liang, J., Wang, Q., Jin, H., Wang, W., Lü, Y., Li, F., Zhou, Y., Zhang, W., Liao, Z., Qiu, Q., Li, Y., Kong, C., Li, Y., Jiao, H., Lu, J., & Jia, J.
Affiliations
  • Capital Medical University (CN)
  • First Affiliated Hospital of Xi'an Jiaotong University (CN)
  • Central South University (CN)
  • Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
  • Zhejiang University (CN)
  • China-Japan Friendship Hospital (CN)
  • Qingdao University (CN)
  • First Affiliated Hospital Zhejiang University (CN)
  • Shanghai Jiao Tong University (CN)
  • Guangzhou Medical University (CN)
  • Shandong University (CN)
  • Wuhan University (CN)
  • Beijing Geriatric Hospital (CN)
  • Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • Tianjin Huanhu Hospital (CN)
  • Zhejiang Provincial People's Hospital (CN)
Corresponding author
  • Lu, Jie
  • Jia, Jianping
ORCID
Venue
Brain
Publisher
Oxford University Press (OUP)
Published
2020-11-14
Volume
144
Issue
3
Pages
924-937
ISSN
  • 0006-8950 (ISSN-L)
  • 1460-2156
DOI
10.1093/brain/awaa364
PMC
PMC8041344
OpenAlex
W3102892253
Cited by
67
References
12
Citations by year
2026: 9 · 2025: 12 · 2024: 13 · 2023: 16 · 2022: 11 · 2021: 5 · 2020: 1
FWCI
5.26
Type
journal article
Language
en
Open access
Licence
Locations
  • Brain (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Funders
  • 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 Municipal Science & Technology Commission (Z201100005520016, Z201100005520017, Z161100000216137)
  • Beijing Municipal Commission of Health and Family Planning (PXM2019_026283_000003)
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
Alzheimer's disease, genetic susceptibility, single nucleotide polymorphisms, disease risk prediction, prediction model, apolipoprotein E, anti-oxidation, neurogenesis, Chinese population, genetic counseling
MeSH terms
Aged, Aged, 80 and over, Alzheimer Disease, Female, Genotype, Humans, Male, Middle Aged, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Asian People, Genome-Wide Association Study

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