Microbial rank

Microbial rank

Microbial Rank SEE ARTICLE ON PAGE 1303 Just as military rank is determined by the strength of performance, the rank of infectious agents is commens...

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Microbial Rank

SEE ARTICLE ON PAGE 1303

Just as military rank is determined by the strength of performance, the rank of infectious agents is commensurate with their disease association. Microbes that clearly cause serious illness are the most respected: the group A streptococcus, Staphylococcus aureus, and human immunodeficiency virus (HIV). However, with recent advances in molecular biology, microbes increasingly are being discovered outside the context of disease. In the past several years, at least three new viruses have been conscripted as causes of the viral hepatitis syndrome alone. The resulting backlog of uncommissioned viruses raises the questions, what principles govern microbial ranking? What is required to conclude that a microbe causes a disease? The most famous criteria for assessing causality were described by Koch, “. . .first, the organism is always found with the disease, in accord with the lesions and clinical stage observed; second, the organism is not found with any other disease; third, the organism, isolated from the one who has the disease and cultured through several generations, reproduces the disease (in a susceptible experimental animal).”1 Unfortunately, appropriate models do not exist for many viruses. In 1965, Bradford Hill expanded the consideration of causality to nine factors: (1) strength, (2) consistency, (3) specificity, (4) temporality, (5) biologic gradient, (6) plausibility, (7) coherence, (8) experimental evidence, and (9) analogy (Table 1).2 While these criteria remain useful, their applicability in the molecular era warrants individual consideration. When large, the magnitude of the association between an infection and a disease is perhaps the most useful indication of causality. The magnitude of the association is typically reflected by an odds ratio or another measure of risk, and is distinct from the level of statistical significance that can be represented by a P value. The finding that persons with hepatocellular carcinoma were more than 100-fold more likely to have hepatitis B infection is a classic example of a strong, causal association.3 Nonetheless, the magnitude of an association would not be expected to be large when an infection is one of several causes of a disease (e.g., Epstein-Barr infection and pharyngitis) or when the disease is a relatively infrequent complication of the infection (essential mixed cryoglobulinemia and hepatitis C virus [HCV] infection). These considerations also undermine the “specificity” re-

Abbreviations: HIV, human immunodeficiency virus; HCV, hepatitis C virus. From the Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD. Received March 19, 2001; accepted March 21, 2001. Address reprint requests to: David L. Thomas, M.D., Associate Professor of Medicine, Division of Infectious Diseases, Johns Hopkins University School of Medicine, 424 N Bond St., Baltimore, MD 21231. Fax: 410-614-7564. Copyright © 2001 by the American Association for the Study of Liver Diseases. 0270-9139/01/3305-0041$35.00/0 doi:10.1053/jhep.2001.24743

quirement. While it is convincing when an infection always causes a single disease (e.g., rabies), this stringent specificity is the exception rather than the rule. For example, hepatitis can be caused by a number of infections that are not typically considered “hepatitis viruses,” principally because liver inflammation is not their cardinal clinical finding. The specificity consideration is germane to the report by Umemura et al. because hepatitis was found in some, but not all, subjects with transfusion-associated SEN-V infection.4 As the investigators point out, this apparent lack of specificity does not exclude SEN-V as the cause of hepatitis in this study, especially because hepatitis occurred more often than expected in those with post-transfusion SEN-V infection. When it comes to the magnitude of the association, large is very helpful, but many valid associations may have modest measures of risk. In the absence of an experimental model as required by Koch, many disease associations are judged by the consistency of the findings. In a legal proceeding, when there is no eye witness (experimental proof), a case can still be made with extensive, consistent circumstantial evidence (clinical associations). Notably, such consistency was absent from the link between GB virus-C and hepatitis found in preliminary but not most subsequent research studies. Conversely, when the causal role of HCV was being questioned shortly after its cloning, the association of HCV infection with cirrhosis was consistently shown and is a case that, though circumstantial, has been accepted. It is too early to judge the SEN-V literature for consistency, since the report by Umemura et al. is the first on disease association.4 A close temporal link between the infection and disease is another attribute that is useful when present, but not when absent. Indeed, one of the most compelling pieces of evidence in the report by Umemura et al. is the link between the acquisition of SEN-V infection and the occurrence of hepatitis.4 In other cases, apparent temporal associations have not been reproduced, and there are a number of infections whose acquisition is not temporally linked to the disease they cause. There was a temporal association of GB virus-C (hepatitis G) infection and hepatitis after transfusion.5 However, it was later appreciated that, although the virus was clearly transmitted by the transfusions, GB virus-C may not have been the causative agent of the post-transfusion hepatitis. Conversely, long disease incubation, as occurs with hepatitis C infection and cirrhosis, may make it difficult to make the temporal link between the onset of disease and infection. A biological gradient or “dose-response” relationship may support the causal link but is rarely the determining factor with infection and disease. While the level of HIV in blood strongly determines the progression to acquired immunodeficiency syndrome,6 the relationship is much less clear for HCV and cirrhosis. In addition, for the pathogenesis of some diseases, a threshold effect may be more reasonable to expect than a dose-response relationship (e.g., Epstein-Barr virus and lymphoma).7 It is helpful when the proposed disease-infection associa-

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HEPATOLOGY Vol. 33, No. 5, 2001

THOMAS

TABLE 1. Factors to Consider When Assessing an Infection as the Cause of a Disease Factor

Strength Consistency Specificity Temporality Biological gradient Biologic plausibility Coherence Experimental evidence Analogy

Comment

Very helpful when association is strong; small magnitude associations may be valid Multiple consistent findings are necessary when experimental proof is not possible Should not be required as many infections cause more than one syndrome Helpful when present, but disease latency may occur Helpful, but “dose-response” relationships should not be required Very helpful especially when the pathogenesis is understood Internal consistency of data is helpful Proves the association but often not possible Similar disease process can be instructive

Adapted from Hill.2

tion is biologically plausible. For example, with candidate hepatitis viruses, it is very useful to show replication in liver. This can be technically difficult, as was illustrated by several contradictory reports regarding detection of GB virus-C replicative intermediates. Nonetheless, if confirmed, detection of SEN-V cDNA in liver samples by Umemura et al. is an important step toward establishing causality.4 As the pathogenesis of many chronic diseases is poorly understood, assessment of biological plausibility is sometimes difficult and should not be used to disqualify an agent with strong epidemiologic linkage to a disease. As microbes increasingly are discovered outside the context of disease, it is also reasonable to recall that microbes do not exist to cause disease. In fact, from an evolutionary perspective, microbial persistence is not enhanced by killing or diminishing the reproductive capability of the host. That is probably why most microbes are not known to cause disease. A healthy large intestine has an average of 1 ⫻ 1011 bacteria per gram, and a number of bacteria are normal residents of the oral mucosa. Most of these bacteria are not even named, and disease occurs when the microbes are absent. While, mucosal bacteria are outside the body, bacteria, fungi, and viruses also have been found in “healthy” tissues that only appear to cause disease in special circumstances, as with immune suppression. For example, Pneumocystis carinii and JC virus can be detected in “normal” lung and kidney, respectively, but cause disease only in immunosuppressed persons.

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Although some organisms recovered from blood may not cause disease, infections probably cause or contribute to many diseases whose etiology is currently unknown. How can we prepare to rank the newly discovered microbes and inevitable new recruits? Recent history, including the report by Umemura et al., underscores the value of prospective studies in settings in which the acquisition of an infection can be clearly delineated, such as following a transfusion.4 It also may be necessary to extend the observation period of such studies and broaden the medical evaluations to examine long-term consequences of transfusion-transmitted infections. Unfortunately, for infections that are uncommon or uncommonly cause disease, it may be difficult and expensive to assess causality in prospective studies. Thus, well-characterized registries of biologically important tissues will be necessary and, when not already present, should be established for idiopathic diseases. In the meantime, the ranks of the members of a growing list of novel microbes need to be considered with respect to the factors discussed above and, as was done by Umemura et al., restraint should be exercised before attributing causality. Acknowledgment: The author thanks Dr. Stuart Ray for thoughtful comments regarding the manuscript. DAVID L. THOMAS, M.D. Division of Infectious Diseases Johns Hopkins University School of Medicine Baltimore, MD REFERENCES 1. Susser M. Causal Thinking in the Health Sciences. Concepts and Strategies in Epidemiology. New York: Oxford University Press, 1973. 2. Hills AB. The environment and disease: association or causation? Proc R Soc Med 1965;58:295-300. 3. Beasley RP, Hwang LY, Lin CC, Chien CS. Hepatocellular carcinoma and hepatitis B virus: a prospective study of 22707 men in Taiwan. Lancet 1981;2:1129-1133. 4. Umemura T, Yeo AET, Sottini A, Moratto D, Tanaka Y, Wang RY-H, Shih JW-K, et al. SEN virus infection and its relationship to transfusion-associated hepatitis. HEPATOLOGY 2001;33:1303-1311. 5. Linnen J, Wages J, Jr., Zhang-Keck ZY, Fry KE, Krawczynski KZ, Alter HJ, Koonin E, et al. Molecular cloning and disease association of hepatitis G virus: A transfusion-transmissible agent. Science 1996; 271:505-508. 6. Mellors JW, Rinaldo CRJ, Gupta P, White RM, Todd JA, Kingsley LA. Prognosis in HIV-1 infection predicted by the quantity of virus in plasma. Science 1996;272:1167-1170. 7. de The G, Geser A, Day NE, Tukei PM, Williams EH, Beri DP, Smith PG, et al. Epidemiological evidence for causal relationship between Epstein-Barr virus and Burkitt’s lymphoma from Ugandan prospective study. Nature 1978;274:756-761.