Identifying the underlying genetic factors influencing these infectious disease phenotypes may help to illuminate how the immune system functions, uncover factors influencing infection susceptibility or resistance, and suggest strategies for the prevention and treatment of infection

Identifying the underlying genetic factors influencing these infectious disease phenotypes may help to illuminate how the immune system functions, uncover factors influencing infection susceptibility or resistance, and suggest strategies for the prevention and treatment of infection. Acknowledgements We thank the participants of the SAFHS and the SAFDGS. well as genetic correlations among pathogens. The pathogens were chosen in part based on suspected involvement in chronic inflammatory diseases including atherosclerosis. Infectious brokers included two bacterial pathogens: and (Bioclone Australia Pty Ltd., Marrickville, N.S.W., Australia); and CMV (Inverness Medical Professional Diagnostics, Palatine, Ill., USA); to 92% for VZV, as previously explained (table ?(table22). Table 1 Information on pedigree associations and households for study participants Pedigree information?Quantity of pedigrees45?Maximum number of generations5?Size of largest pedigree, n95?Average sibship size (range)3.2 (2C11)Familial relationships, observed pairs?Parent-offspring1,034?Monozygotic twins3?Full siblings1,143?Half siblings194?Grandparent-grandchild357?Avuncular2,411?Half avuncular379?First cousins2,608Household information?Quantity of households658?Average household size (range)1.9 (1C14)?Quantity of households 1 individual289?Average household size for households 1 individual (range)3.3 (2C14)?Quantity of spousal pairs residing in same household115 Open in a separate window Table values represent only study participants (n = 1,227), actual pedigree sizes, pairs of familial associations and household sizes may actually be larger due to presence of unphenotyped relatives/co-inhabitants. Table 2 Seroprevalence estimates for pathogens examined in this study IA = Influenza A; IB = Influenza B. Upper right (above and to the right of the diagonal) = correlations; lower left (below and to Mmp2 the left of the diagonal) = p values. Bold = Point-wise significant at p 0.05. Note that pathogens included here are p-Coumaric acid only those for which the quantitative antibody levels (A) and the dichotomous serostatus phenotypes (B) were significantly heritable in the univariate analysis. Replication To assess the robustness of our heritability estimates, we measured antibody levels (using identical serological assays), and estimated heritabilities, for eight of the investigated pathogens in a separate Mexican American cohort consisting of participants in the SAFDGS [9,10]. Pathogens compared between the two studies included in this study (h2 = 0.35) is lower than that reported for any previous study (h2 = 0.57), and while the other study reported significant shared environmental effects, this study does not [4]. The phenotypes examined here are largely the result of exposure to naturally occurring antibodies, in other words antibodies that were produced in response to infectious brokers encountered in the p-Coumaric acid environment, rather than through routine vaccination. A possible exception includes the influenza viruses, given that vaccine was available against these pathogens at the time p-Coumaric acid the study samples were collected (1991C1995). However, it is not clear what effect this may have had, if any, around the influenza A and B antibody level measurements used in our study in part because annual influenza vaccines were less common when these samples were collected almost two decades ago, in particular among Hispanics who historically have significantly lower influenza vaccination rates than the general US public [27,28,29]. In any case, overall our study provides obvious evidence that naturally acquired infectious disease antibody level characteristics are significantly heritable, and may therefore be viewed as partly genetic characteristics. The fact that antibody levels can vary from person to person as a function of genetics, rather than exposure alone, should be borne in mind when interpreting antibody test results in a clinical establishing. Our bivariate analyses show that some genetic factors appear to be shared between some closely related pathogens, such as different influenza computer virus strains. However, we did not observe obvious evidence for genetic factors that influence antibody levels to all pathogens or even classes of pathogens (such as herpesviruses). For most pathogen pairs, our observations are consistent with host genetic factors influencing antibody levels being pathogen specific. While our study demonstrates that genetic factors have a strong influence on antibody levels for many pathogens, shared environment (modeled as co-habitation) was also a significant contributing factor to the serological phenotypes for some pathogens. This may be due to direct transmission of contamination between relatives, for example, through coughing or kissing, due to shared exposure to infectious brokers such as via drinking water or domestic pets in the household, or due to shared behavioral practices, such as hand washing, food preparation, etc., among family members. The decision to focus on antibody levels, which are not a direct assessment of the presence or absence of infectious brokers, complicates the interpretation of our results, due to the nature of serological data. The presence of antibodies indicates a past or present contamination, but this does not necessarily correlate with protection [30]. In our study, it is not clear whether, for example, a high antibody level represents success in warding off infection, or whether the immune system was less efficient at dealing with the invading pathogen, resulting in a prolonged infection. It is also possible that elevated levels of antibody are related to more recent, repeated, or stronger dose exposures to the infectious agent [31,32]..