Lipoprotein Subclass Analysis (for research use only)

Lipoproteins are supramolecular assemblies that transport water-insoluble lipids in blood. Lipoproteins also carry apolipoproteins, which determine structure and function. Apolipoproteins, a monolayer of amphiphilic phospholipids and cholesterol embedded therein, constitute the surface of the lipoproteins that 'hide' the lipids from the aqueous surrounding. The inner core mainly consists of triglycerides and esterified cholesterol.

Lipoproteins are commonly classified into five main groups:

• ƒƒChylomicrons
• Very Low Density Lipoproteins (VLDL)
• ƒƒIntermediate Density Lipoproteins (IDL)
• ƒƒLow Density Lipoproteins (LDL)
• ƒƒHigh Density Lipoproteins (HDL)

In the context of cardiovascular risk assessment, the lipoprotein class-specific concentrations of cholesterol and triglycerides are of interest beyond their total concentrations within the plasma. There is a strong indication that additional sub-classification of of lipoproteins could improve cardiovascular risk prediction.

The Bruker B.I.-LISA lipoprotein panel offers significant benefits versus the current testing modality, e.g. the ultracentrifugation method, which typically takes 1 week persample. Ultracentrifuges currently handle up to 16 samples in parallel; however, the procedure requires repeated, precise manual interaction. For VLDL subclass analysis, anultracentrifuge with adjustable angles is required. Alternative approaches are therefore sought.

Bruker has led a project to establish lipoprotein subclass analysis based on ¹H-Nuclear Magnetic Resonance (¹H-NMR) spectroscopy of blood plasma or serum samples, using regression analysis of ultracentrifugation results.

The objective was to provide an analytical method that:

• Determines cholesterol, phospholipids, triglycerides, apolipoproteins A1, A2, B and LDL particle numbers for lipoprotein main and subclasses for plasma and serum.
• ƒƒWorks at high throughput (up to 150 samples per day in high quality regular screening) at low cost per sample, under full automation, simple sample preparation and automatic report generation
• Provides sufficient accuracy at highest reproducibility and complete transferability from instrument to instrument.

The method of choice is based on the analysis of signals in the ¹H-NMR spectrum that are related to the lipoproteins. Differences in lipoprotein composition, size and density translate into respective signal line shape differences, which can be used to extract information on lipoprotein main and subclasses (see figure 1).

A regression model had to be developed, using a training data set which consists of:

• Lipoprotein analytes from total plasma and ultra-centrifugation-based main and subclasses
• ƒƒ¹H-NMR spectra of the same sample set

Once the regression model was established, a prediction algorithm calculates the lipoprotein analytes directly from the ¹H-NMR spectra of new plasma or serum samples, without further need for ultra-centrifugation.

Using this ¹H-NMR approach, information could be extracted about lipoprotein related information on:

• Plasma and serum
• The main VLDL, IDL, LDL and HDL classes
• Six VLDL subclasses VLDL-1 to VLDL-6 (sorted according to increasing density and decreasing size, respectively)
• Six LDL sub-classes LDL-1 to LDL-6
• Four HDL-subclasses HDL-1 to HDL-4

Information consists of concentrations of lipids, i.e.cholesterol, free cholesterol, phospholipids, triglycerides, concentrations of apolipoproteins Apo-A1, ApoA2 and Apo-B and the LDL particle numbers. Table 1 shows all parameterscalculated by the ¹H-NMR lipoprotein analysis. Figure 1 shows the front page of the automatic report (B.I.-LISA).

• ƒƒLower cost than ultracentrifugation
• ƒƒMuch faster turnaround time – minutes versus days
• Completely automated and simple to run (e.g. by an MTA)
• Equal sensitivity and specificity as ultracentrifugation
• Small sample volume (500 microliter) – better patient compliance
• Straightforward sample preparation
• ƒƒNo direct contact between sample and device
• Spectra can be used for multiple types of analysis

• ƒƒIVDr platform at 600 MHz
• Use of Bruker SOPs for plasma/serum
• Absolute temperature, solvent suppression and quantification reference sample must be checked regularly (preferably daily)
• Access to Bruker Data Analysis server for fully automated remote analysis (transfer of spectra after measurement to Bruker server via private ftp, back-transfer of result report)