+1 Recommend
    • Review: found
    Is Open Access

    Review of 'Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease'

    Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s diseaseCrossref
    Average rating:
        Rated 4.5 of 5.
    Level of importance:
        Rated 4 of 5.
    Level of validity:
        Rated 4 of 5.
    Level of completeness:
        Rated 5 of 5.
    Level of comprehensibility:
        Rated 5 of 5.
    Competing interests:

    Reviewed article

    • Record: found
    • Abstract: found
    • Article: found
    Is Open Access

    Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease

    For Alzheimer’s disease–a leading cause of dementia and global morbidity–improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer’s disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer’s disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer’s disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer’s disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer’s disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution. Alzheimer’s disease is a leading cause of dementia and global morbidity. Despite decades of research, disease modifying therapies remain elusive. One possible explanation for failed clinical trials is intervention too late in the disease process when therapies are unlikely to be effective. Here, we developed a genetic predictor for Alzheimer’s disease allowing us to identify asymptomatic individuals at increased risk of developing Alzheimer’s disease. We next measured the levels of 3,231 proteins in the blood of middle-aged, healthy individuals and found proteins whose levels were changed in individuals with a high genetic risk of developing Alzheimer’s disease. Several of these proteins have not previously been studied in Alzheimer’s. Our study suggests a method to identify high genetic risk individuals during the presymptomatic phase of disease, enabling us to discover new protein-based biomarkers in the early stages of disease progression.

      Review information

      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

      ScienceOpen disciplines:

      Review text

      The manuscript described a method to identify the high risk individuals with Alzheimer's disease, by combining polygenetic predictor and proteomic signature. Since protein expression is closer to pathological phenotypes, the combination of DNA variations and protein abundances served as a good approach for disease diagnostics.

      My only concern is about the proteomic method. Why was the aptamer-based profiling performed in proteomic analysis, instead of unbiased label-free proteomics? What is the advantages of using aptamer-based method here?


      Comment on this review

      Version and Review History