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Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS.

Zhang Y, Wu P, Luo Y, Tao C - J Biomed Semantics (2015)

Bottom Line: Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety.Specifically, we compared network properties of (1) vaccine - adverse event association network based on reports collected over a 23 year period as well as each year; and (2) sex-specific vaccine-adverse event association network.We observed that (1) network diameter and average path length don't change dramatically over a 23-year period, while the average node degree of these networks changes due to the different number of reports during different periods of time; (2) vaccine - adverse event associations derived from different sexes show sex-associated patterns in sex-specific vaccine-AE association networks.

View Article: PubMed Central - PubMed

Affiliation: Division of Biostatistics and Bioinformatics, University of Maryland Greenebaum Cancer Center, Baltimore, USA ; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, USA.

ABSTRACT

Background: Vaccines are one of the most important public health successes in last century. Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety. Due to the limitations of adverse event (AE) data from clinical trials and post-approval surveillance systems, novel computational approaches are needed to organize, visualize, and analyze such high-dimensional complex data.

Results: In this paper, we proposed a network-based approach to investigate the vaccine-AE association network from the Vaccine AE Reporting System (VAERS) data. Statistical summary was calculated using the VAERS raw data and represented in the Resource Description Framework (RDF). The RDF graph was leveraged for network analysis. Specifically, we compared network properties of (1) vaccine - adverse event association network based on reports collected over a 23 year period as well as each year; and (2) sex-specific vaccine-adverse event association network. We observed that (1) network diameter and average path length don't change dramatically over a 23-year period, while the average node degree of these networks changes due to the different number of reports during different periods of time; (2) vaccine - adverse event associations derived from different sexes show sex-associated patterns in sex-specific vaccine-AE association networks.

Conclusions: We have developed a network-based approach to investigate the vaccine-AE association network from the VAERS data. To our knowledge, this is the first time that a network-based approach was used to identify sex-specific association patterns in a spontaneous reporting system database. Due to unique limitations of such passive surveillance systems, our proposed network-based approaches have the potential to summarize and analyze the associations in passive surveillance systems by (1) identifying nodes of importance, irrespective of whether they are disproportionally reported; (2) providing guidance on sex-specific recommendations in personalized vaccinology.

No MeSH data available.


Related in: MedlinePlus

Comparison of vaccine similarity in different sexes. a Hierarchical analysis of vaccines based on association information in female reports; b Hierarchical analysis of vaccines based on association information in male reports; c Dendrogram of vaccine similarity in female reports; d Dendrogram of vaccine similarity in male reports
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Fig3: Comparison of vaccine similarity in different sexes. a Hierarchical analysis of vaccines based on association information in female reports; b Hierarchical analysis of vaccines based on association information in male reports; c Dendrogram of vaccine similarity in female reports; d Dendrogram of vaccine similarity in male reports

Mentions: We further investigated whether vaccine-AE associations are different between genders. We constructed sex-specific vaccine-AE association networks by computing the PRR based on reports only from female/male populations. There are 49,616 and 51,578 significant vaccine-AE associations (i.e., PRR > 1) in female and male populations, respectively. The network properties of these two sex-specific association networks are similar with overall association network (Table 1). We clustered the vaccines based on their association indexes calculated by their associations with AEs. In Fig. 3a and b, we observed different similarity patterns in female (Fig. 3a and male (Fig. 3b). For instance, HBHEPB, ROTH1, PNC13, DTAP IPVHIB, PNC, ROTHB5, DTAPHEPBIP, HIBV, DTAP, and IPV were clustered together based on their associations with adverse events in the female population. Besides most of the vaccines that were grouped in the female population, we also found four more vaccines in the same group in the male population, including PNC, HEP, VARCEL, and MMR. Similarly, while DIPHIB, DTP, and OPV were tightly clustered in the male population, RV was also grouped in this cluster in the female population. The dendrograms indicate the same differences between two populations (Fig. 3c and d). These results indicate that there are indeed sex-specific reponse differences after vaccine injection.Fig. 3


Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS.

Zhang Y, Wu P, Luo Y, Tao C - J Biomed Semantics (2015)

Comparison of vaccine similarity in different sexes. a Hierarchical analysis of vaccines based on association information in female reports; b Hierarchical analysis of vaccines based on association information in male reports; c Dendrogram of vaccine similarity in female reports; d Dendrogram of vaccine similarity in male reports
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4541751&req=5

Fig3: Comparison of vaccine similarity in different sexes. a Hierarchical analysis of vaccines based on association information in female reports; b Hierarchical analysis of vaccines based on association information in male reports; c Dendrogram of vaccine similarity in female reports; d Dendrogram of vaccine similarity in male reports
Mentions: We further investigated whether vaccine-AE associations are different between genders. We constructed sex-specific vaccine-AE association networks by computing the PRR based on reports only from female/male populations. There are 49,616 and 51,578 significant vaccine-AE associations (i.e., PRR > 1) in female and male populations, respectively. The network properties of these two sex-specific association networks are similar with overall association network (Table 1). We clustered the vaccines based on their association indexes calculated by their associations with AEs. In Fig. 3a and b, we observed different similarity patterns in female (Fig. 3a and male (Fig. 3b). For instance, HBHEPB, ROTH1, PNC13, DTAP IPVHIB, PNC, ROTHB5, DTAPHEPBIP, HIBV, DTAP, and IPV were clustered together based on their associations with adverse events in the female population. Besides most of the vaccines that were grouped in the female population, we also found four more vaccines in the same group in the male population, including PNC, HEP, VARCEL, and MMR. Similarly, while DIPHIB, DTP, and OPV were tightly clustered in the male population, RV was also grouped in this cluster in the female population. The dendrograms indicate the same differences between two populations (Fig. 3c and d). These results indicate that there are indeed sex-specific reponse differences after vaccine injection.Fig. 3

Bottom Line: Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety.Specifically, we compared network properties of (1) vaccine - adverse event association network based on reports collected over a 23 year period as well as each year; and (2) sex-specific vaccine-adverse event association network.We observed that (1) network diameter and average path length don't change dramatically over a 23-year period, while the average node degree of these networks changes due to the different number of reports during different periods of time; (2) vaccine - adverse event associations derived from different sexes show sex-associated patterns in sex-specific vaccine-AE association networks.

View Article: PubMed Central - PubMed

Affiliation: Division of Biostatistics and Bioinformatics, University of Maryland Greenebaum Cancer Center, Baltimore, USA ; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, USA.

ABSTRACT

Background: Vaccines are one of the most important public health successes in last century. Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety. Due to the limitations of adverse event (AE) data from clinical trials and post-approval surveillance systems, novel computational approaches are needed to organize, visualize, and analyze such high-dimensional complex data.

Results: In this paper, we proposed a network-based approach to investigate the vaccine-AE association network from the Vaccine AE Reporting System (VAERS) data. Statistical summary was calculated using the VAERS raw data and represented in the Resource Description Framework (RDF). The RDF graph was leveraged for network analysis. Specifically, we compared network properties of (1) vaccine - adverse event association network based on reports collected over a 23 year period as well as each year; and (2) sex-specific vaccine-adverse event association network. We observed that (1) network diameter and average path length don't change dramatically over a 23-year period, while the average node degree of these networks changes due to the different number of reports during different periods of time; (2) vaccine - adverse event associations derived from different sexes show sex-associated patterns in sex-specific vaccine-AE association networks.

Conclusions: We have developed a network-based approach to investigate the vaccine-AE association network from the VAERS data. To our knowledge, this is the first time that a network-based approach was used to identify sex-specific association patterns in a spontaneous reporting system database. Due to unique limitations of such passive surveillance systems, our proposed network-based approaches have the potential to summarize and analyze the associations in passive surveillance systems by (1) identifying nodes of importance, irrespective of whether they are disproportionally reported; (2) providing guidance on sex-specific recommendations in personalized vaccinology.

No MeSH data available.


Related in: MedlinePlus