Chunfei Wu

Chunfei Wu

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Materials characterisation - Liquid – Composition analysis - Nuclear magnetic resonance (NMR) - Application of NMR (liquid)

A Nuclear Magnetic Resonance Spectroscopy Method in Characterization of Blood Metabolomics for Alzheimer’s Disease

10.3390/metabo12020181

“There is currently a crucial need for improved diagnostic techniques and targeted treatment methods for Alzheimer’s disease (AD), a disease which impacts millions of elderly individuals each year. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease. In this report, we present our AD metabolomics results measured with high resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) on human blood plasma samples obtained from AD and non-AD subjects. Our study centers on developments of AD and non-AD metabolomics differentiating models with procedures of quality assurance (QA) and quality control (QC) through pooled samples. Our findings suggest that analysis of blood plasma samples using HRMAS NMR has the potential to differentiate between diseased and healthy subjects, which has important clinical implications for future improvements in AD diagnosis methodologies.”

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4.3. HRMAS NMR

All NMR measurements were conducted on a Bruker AVANCE III HD 600 MHz spectrometer (Bruker BioSpin, Billerica, MA, USA). Before measurements, all samples were allowed to thaw for approximately an hour on ice. After being vortexed, 10 μL of the individual plasma sample and 2.5 μL of D2O, or 12 μL of the pooled controls, were added to the 4 mm rotor, with a 12 μL Kel-f insert. HRMAS NMR data were collected at 4 °C, with a spinning rate of 3600 Hz and with a rotor synchronized CPMG method. The other spectral conditions included: recycle time 5 s, 100 CPMG p pulses with a total mixing time of 55.56 ms, 16 K data points with a total acquisition time of 0.85 s, and a spectral width of 16 ppm.

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2.1. HRMAS NMR Accuracy Analyzed by QA/QC Pooled Plasma Controls

To test and evaluate our systematic QA/QC, we pooled 16 AD and 14 non-AD blood plasmas to create 6 pooled control samples. Figure 1A presents the comparison between the average spectrum of all 35 individual samples, and the average spectrum of the 6 pooled controls. Statistically significant linear correlations with a tangent close to 1.0 (t = 0.99 ± 0.03, with r2 = 0.93 ± 0.02, and p = 3.84 ± 3.82 e−17) were observed between the spectral intensities of the 36 identified regions measured from the mean, with standard errors (SE) indicated by the horizontal error bars for the 35 individual samples and each of the pooled controls, as shown in Figure 1B. These statistically significant linear correlations with tangents close to 1.0 suggest the overall systematic QA/QC satisfaction of the data. Upon confirming the quality of the data, we proceeded with evaluating the spectral intensity data measured from individual plasma samples. Of special note, the three regions that displayed large SEs all included the measurable lipids.
Metabolites 12 00181 g001 550
Figure 1. HRMAS NMR of pooled plasma control samples. (A) A comparison between the averaged spectrum calculated from all 35 individual samples, and the averaged spectrum calculated from the six pooled controls. The color shaded areas in the spectra represented standard deviations measured from 35 individual and six pooled samples, respectively. (B) Linear correlations between spectral regions between each pooled control sample and the mean of individual samples, with standard errors presented as error bars, indicating sufficient systematic QA/QC validation.

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