Proteomic fingerprinting for biomarker discovery has been applied in the past decade to a variety of disease states, particularly in the sphere of cancer diagnostics [26, 27] . The power of this approach is reflected by the recent granting of FDA approval of a novel blood test derived from a SELDI-based fingerprinting method, for distinguishing malignant from benign ovarian tumours [27, 28] . In many infectious diseases, there are clinically important distinctions to be made between different manifestations associated with the same underlying pathogen. For example, distinguishing colonization or latent disease from active infection has obvious clinical and therapeutic implications. TB is a clear case in point. Proteomic fingerprinting has enormous potential for defining and distinguishing these disease states but has only recently received attention in this area [12] [13] [14] [29] [30] [31] . Because the circulation samples deep tissues throughout the body, local proteomic changes in organs such as the lungs can be reflected in the plasma proteome. Moreover, host modulation by the pathogen is likely to generate changing patterns of protein expression associated with different clinical manifestations. Thus the plasma proteomic response is a plausible index of disease state. Proteomic patterns are highly dynamic and it may be possible to define those that reflect stages in progression from latency to active disease. However, the complexity of the plasma proteome with its enormous dynamic range of solute concentrations means that detection of informative lower abundance proteins is particularly challenging. It is possible that differences between active TB and LTBI in symptomatic patients are reflected better by such lower abundance proteins not easily detectable in crude plasma. This may explain the higher specificity for active TB obtained from prefractionated as compared to the crude plasma spectra.