DISPATCHES
1074
Emerging Infectious Diseases • v/eid • Vol. 13, No. 7, July 2007
Little Evidence for Genetic Susceptibility to In fl uenza A (H5N1) from Family Clustering Data Virginia E. Pitzer,* Sonja J. Olsen,† Carl T. Bergstrom,‡ Scott F. Dowell,†
and Marc Lipsitch*
The apparent clustering of human cases of in fl uenza A (H5N1) among blood relatives has been considered as evi-dence of genetic variation in susceptibility. We show that, by chance alone, a high proportion of clusters are expected to be limited to blood relatives when infection is a rare event.
S
ince December 2003, 36 family clusters among 261 con fi rmed human cases of in fl uenza A (H5N1) have been documented (1,2). These clusters range in size from 2 to 8 infected persons; in only 4 clusters were 2 unrelated family members (e.g., husband and wife) infected. This pat-tern has been considered by the World Health Organization as evidence of genetic variation in susceptibility (3–5), but we show this observation provides little grounds for this in-ference. We describe a null model in which nuclear families experience a common exposure to an avian in fl uenza virus. The observed degree of clustering in blood relatives is con-sistent with that expected by chance alone in the absence of genetic variation in susceptibility; other features of the data are also consistent with the null model.
Our model assumes all persons are equally susceptible, such that they have the same probability of infection, τ, and ignores possible human-to-human transmission (see online Technical Appendix, available from v/EID/content/13/7/1074-Techapp.htm). The number of infected family members follows a binomial distribution with mean n τ, where n  is the number of exposed persons in each fam-ily. A cluster is de fi ned as a family in which >1 person is infected; clusters are limited to blood relatives unless both parents are infected.
We compare our model to the observation that 32 of 36 clusters that occurred from December 2003 to Decem-ber 2006 consisted only of blood relatives (p B  = 0.89, 95%
con fi dence interval 0.74–0.97; Table in online Techni-cal Appendix). When the probability of infection is low,
most clusters consist of 2 infected family members, and by
simple combinatorics, these 2 are usually blood relatives,
which is consistent with the observed date (Figure 1).
For a given a nuclear family size, the null model also
predicts the proportion of all cases that are part of a clus-ter and the average number of cases per cluster. Neither of
these measures follows a simple distribution; we therefore
use simulated data to determine what ranges of our param-eters (τ and n ) are consistent with the observed degree of
clustering both in families and among blood relatives. We estimate the mean and 95% prediction intervals for the pro-portion of cases occurring in clusters when there are 261 cases, and for the average number of cases per cluster when there are 36 clusters. The expected proportion of cases oc-curring in clusters is similar to the observed data when the probability of infection is low (τ<0.15) (Figure 2). The observed average number of cases per cluster, however, is consistent with slightly higher probabilities of infection, larger family sizes, or both (Figure 2).
The discrepancy between the number of cases per clus-ter and the proportion of cases in clusters may be due to be-tween-family variation in τ. If the probability of infection is low for members of most exposed families and higher for members of a few exposed families, then most cases may come from families in which τ is low, but most of the clusters will occur among families for which τ was higher. This
will lead to a lower proportion of cases occurring in clusters and a higher average number of cases per cluster, as is observed. Although it is possible that such variation may be genetic, it could also result from between-house-hold heterogeneity in intensity of exposure to infected birds
*Harvard School of Public Health, Boston, Massachusetts, USA; †Centers for Disease Control and Prevention, Atlanta, Georgia, USA; and ‡University of Washington, Seattle, Washington, USA Figure 1. Proportion of clusters limited to blood relatives versus the probability of infection (τ) under the null hypothesis (no variation in susceptibility). Point estimate of the observed data is represented by the solid black line; the shaded region represents the 95% con fi
dence interval.
Little Evidence for Genetic Susceptibility to In fl uenza
Emerging Infectious Diseases • v/eid • Vol. 13, No. 7, July 2007
1075
(or intensity of shedding in birds to which different house-holds are exposed), household hygiene, living conditions, and the like. Human-to-human transmission of the virus could also lead to larger than
expected cluster sizes because having >1 case(s) within a family would increase the risk of subsequent cases occurring, and it could not be ruled out in several clusters (6,7).
Qualitatively, the data suggest the existence of nonge-netic, between-household variation in risk. If such nonge-netic variation were absent, then in any given village, nearly all pairs of cases occurring among unrelated persons in the same village would be in different households. Roughly, the chance that a pair of cases in unrelated persons in a vil-lage would be from the same household as opposed to dif-ferent households would be 1/H , where H  is the number of households in a village. With 4 pairs of cases in unrelated persons in the same household, ≈4H  pairs of cases would be expected within a village, mostly in different households. If the average village size of ≈138 households estimated for an area of Thailand (8) is typical, then if members of all households in a village were at equal risk, we would expect to see far more pairs of unrelated cases within a village than have actually been observed (4H  ≈550 pairs of cases in unrelated persons, which greatly exceeds the observed 261 total cases). Clearly, this argument is only heuristic, but when this argument is combined with the likelihood of biologic and behavioral differences between households, it seems likely that τ would vary considerably from 1 house-hold to another.
Furthermore, the model does not account for addition-al individual variability in susceptibility possibly r
elated to age, level of exposure, or other risk factors. If younger persons have a higher risk for infection or likelihood of exposure, clustering would be promoted, primarily with-in blood relatives, because siblings would be more likely than either parent to become infected. Approximately half of all cases have occurred in those <20 years of age (9).
Similarly, if female persons (for example) were at higher risk for exposure, infection, or both, then clusters including non–blood relatives (e.g., spouses) would tend to include the low-risk sex and thus be less probable. Female persons of ages 10–29 years were slightly overrepresented among laboratory-con fi rmed case-patients, but the difference was not statistically signi fi cant (9).
The null model presented here is not designed to cap-ture all of the heterogeneities in exposure and complexity of real families exposed to in fl uenza subtype H5N1. Rather, it simply illustrates that a large proportion of family clus-ters limited to blood relatives may occur by chance in the absence of genetic variation in susceptibility, particularly when the probability of infection is low and family sizes are large. Although genetic heterogeneity may possibly contribute to the clustering of avian in fl uenza cases within blood relatives, it is neither a necessary nor the most likely explanation for the data currently available.
This work was supported by US National Institutes of Health grants T32 AI07535 (V.E.P.) and cooperative agreement 5U01GM076497 (Models of Infectious Disease Agent Study [M.L.]).
Ms Pitzer is a Doctor of Science candidate in the Depart-ment of Epidemiology at Harvard School of Public Health. Her research interests include epidemiologic methods for investigat-ing emerging infectious diseases.References
1.  Olsen SJ, Ungchusak K, Sovann L, Uyeki TM, Dowell SF, Cox NJ,
et al. Family clustering of avian in fl uenza A (H5N1). Emerg Infect Dis. 2005;11:1799–801.
2.  World Health Organization. Cumulative number of con fi rmed hu-man cases of avian in fl uenza A/(H5N1) reported to WHO. 2006.
[cited 2007 Apr 12]. Available  from www.who.int/csr/disease/avian_in fl
uenza/country/cases_table_2006_12_27/en/index.html
Figure 2. Relationship between
data simulated under the null model and the observed pattern of family clustering for A) the proportion of cases occurring in clusters (given 261 total cases) and B) the average number of cases per cluster (given 36 clusters). Estimates of the mean are represented by solid lines; the shaded regions between the dotted lines show 95% prediction intervals for 1,000 simulations. The observed data are represented by the solid black lines.
DISPATCHES
1076 Emerging Infectious Diseases • v/eid • Vol. 13, No. 7, July 2007
3.  World Health Organization. In fl uenza research at the human and ani-mal interface. 2006. [cited 2006 Nov 3]. Available from www.
who.int/csr/resources/publications/influenza/who_cds_epr_gip_2006_3c.pdf
4.  Perdue ML, Swayne DE. Public health risk from avian in fl uenza
viruses. Avian Dis. 2005;49:317–27.
5.  Beigel JH, Farrar J, Han AM, Hayden FG, Hyer R, de Jong MD, et
al. Avian in fl uenza A (H5N1) infection in humans. N Engl J Med. 2005;353:1374–85.
6.  Ungchusak K, Auewarakul P, Dowell SF, Kitphati R, Auwanit W,
documented evidencePuthavathana P, et al. Probable person-to-person transmission of avian in fl uenza A (H5N1). N Engl J Med. 2005;352:333–40.
7.  Butler D. Family tragedy spotlights fl u mutations. Nature.
2006;442:114–5.
8.  Longini IM Jr, Nizam A, Xu S, Ungchusak K, Hanshaoworakul W,
Cummings DA, et al. Containing pandemic in fl uenza at the source. Science. 2005;309:1083–7.  9.  Epidemiology of WHO-con fi rmed human cases of avian in fl uenza A
(H5N1) infection. Wkly Epidemiol Rec. 2006;81:249–57.Address for correspondence: Virginia E. Pitzer, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Ave,
Boston,MA02115,USA;email:********************.edu

版权声明：本站内容均来自互联网，仅供演示用，请勿用于商业和其他非法用途。如果侵犯了您的权益请与我们联系QQ:729038198，我们将在24小时内删除。