Dataset Information

Prediction of P-tau/Aβ42 in the cerebrospinal fluid with blood microRNAs in Alzheimer’s disease

ABSTRACT:

Background

The most common biomarkers of Alzheimer’s disease (AD) are amyloid β (Aβ) and tau, detected in cerebrospinal fluid (CSF) or with positron emission tomography imaging. However, these procedures are invasive and expensive, which hamper their availability to the general population. Here, we report a panel of microRNAs (miRNAs) in serum that can predict P-tau/Aβ42 in CSF and readily differentiate AD from other dementias, including vascular dementia (VaD), Parkinson disease dementia (PDD), behavioral variant frontotemporal dementia (bvFTD), and dementia with Lewy body (DLB).

Methods

RNA samples were extracted from the participant’s blood. P-tau/Aβ42 of CSF was examined for diagnostic purposes. A pilot study (controls, 21; AD, 23), followed by second (controls, 216; AD, 190) and third groups (controls, 153; AD, 151), is used to establish and verify a predictive model of P-tau/Aβ42 in CSF. The test is then applied to a fourth group of patients with different dementias (controls, 139; AD,155; amnestic mild cognitive impairment [aMCI], 55; VaD, 51; PDD, 53; bvFTD, 53; DLB, 52) to assess its diagnostic capacity.

Results

In the pilot study, 29 upregulated and 31 downregulated miRNAs in the AD group were found. In Dataset 2, these miRNAs were then included as independent variables in the linear regression model. A seven-microRNA panel (miR-139-3p, miR-143-3p, miR-146a-5p, miR-485-5p, miR-10a-5P, miR-26b-5p, and miR-451a-5p) accurately predicted values of P-tau/Aβ42 of CSF. In Datasets 3 and 4, by applying the predicted P-tau/Aβ42, the predictive model successfully differentiates AD from controls and VaD, PDD, bvFTD, and DLB.

Conclusions

This study suggests that the panel of microRNAs is a promising substitute for traditional measurement of P-tau/Aβ42 in CSF as an effective biomarker of AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12916-021-02142-x.

SUBMITTER: Jia L

PROVIDER: S-EPMC8591889 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Alzheimer's Disease (AD) is a complex and multifactorial disease. While large genome-wide association studies have had some success in identifying novel genetic risk factors for AD, case-control studies are less likely to uncover genetic factors that influence progression of disease. An alternative approach to identifying genetic risk for AD is the use of quantitative traits or endophenotypes. The use of endophenotypes has proven to be an effective strategy, implicating genetic risk factors in several diseases, including anemia, osteoporosis and heart disease. In this study we identify a genetic factor associated with the rate of decline in AD patients and present a methodology for identification of other such factors. We have used an established biomarker for AD, cerebrospinal fluid (CSF) tau phosphorylated at threonine 181 (ptau(181)) levels as an endophenotype for AD, identifying a SNP, rs1868402, in the gene encoding the regulatory sub-unit of protein phosphatase B, associated with CSF ptau(181) levels in two independent CSF series (P(combined) = 1.17 x 10(-05)). We show no association of rs1868402 with risk for AD or age at onset, but detected a very significant association with rate of progression of disease that is consistent in two independent series (P(combined) = 1.17 x 10(-05)). Our analyses suggest that genetic variants associated with CSF ptau(181) levels may have a greater impact on rate of progression, while genetic variants such as APOE4, that are associated with CSF A?(42) levels influence risk and onset but not the rate of progression. Our results also suggest that drugs that inhibit or decrease tau phosphorylation may slow cognitive decline in individuals with very mild dementia or delay the appearance of memory problems in elderly individuals with low CSF A?(42) levels. Finally, we believe genome-wide association studies of CSF tau/ptau(181) levels should identify novel genetic variants which will likely influence rate of progression of AD.