The particle subclasses of different size that comprise the major dens
ity classes of plasma lipoproteins (VLDL, LDL, HDL) do not all exhibit
the same associations with coronary artery disease (CAD). Thus, indiv
iduals with comparable levels of LDL and HDL may be at very different
risk of CAD owing to underlying differences in subclass distribution,
All current methods to separate and quantify lipoprotein subclasses ar
e time-consuming and labor-intensive, and, therefore, unsuitable for l
arge clinical research studies or routine assessment of CAD risk in th
e general population, We describe here a spectroscopic approach to lip
oprotein subclass quantification that is rapid and efficient, allowing
the simultaneous, automated quantification of 6 VLDL, 4 LDL, and 5 HD
L subclasses in under 1 minute, The process, which employs proton nucl
ear magnetic resonance (NMR) spectroscopy, exploits knowledge of the n
atural particle size-dependent spectral differences that exist among t
he subclasses, By avoiding the need for any physical separation steps
or reagents, high throughput rates are possible and most sources of an
alytical error are eliminated, This combination, plus the large inform
ation content of each NMR LipoProfile, makes the NMR method an attract
ive, cost-effective alternative to existing clinical means of assessin
g and managing CAD risk.