Role of genetic heterogeneity in determining the epidemiological severity of H1N1 influenza

• Published in: PLoS computational biology Vol. 14; no. 3; p. e1006069
• Main Authors: Sambaturu, Narmada, Mukherjee, Sumanta, López-García, Martín, Molina-París, Carmen, Menon, Gautam I, Chandra, Nagasuma
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21-03-2018; Public Library of Science (PLoS)
• Subjects: Acids; Alleles; Applied mathematics; Bacterial infections; Bioinformatics; Biology; Biology and life sciences; Computer Simulation; Disease Outbreaks; Disease Susceptibility - epidemiology; Epidemics; Epidemiology; Epitopes; Ethnicity; Ethnicity - genetics; Gene expression; Gene frequency; Gene sequencing; Genetic aspects; Genetic diversity; Genomes; Health aspects; Heterogeneity; Histocompatibility antigen HLA; Humans; Immune response; Immune system; Immunology; Infectious diseases; Influenza; Influenza A Virus, H1N1 Subtype - genetics; Influenza A Virus, H1N1 Subtype - immunology; Influenza, Human - epidemiology; Medicine and Health Sciences; Minority & ethnic groups; Outbreaks; Pandemics; People and Places; Population; Population genetics; Population studies; Populations; Software; Supervision; Swine flu; Tracks (paths); Trends; United Kingdom > UK; India
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1006069

Genetic differences contribute to variations in the immune response mounted by different individuals to a pathogen. Such differential response can influence the spread of infectious disease, indicating why such diseases impact some populations more than others. Here, we study the impact of population-level genetic heterogeneity on the epidemic spread of different strains of H1N1 influenza. For a population with known HLA class-I allele frequency and for a given H1N1 viral strain, we classify individuals into sub-populations according to their level of susceptibility to infection. Our core hypothesis is that the susceptibility of a given individual to a disease such as H1N1 influenza is inversely proportional to the number of high affinity viral epitopes the individual can present. This number can be extracted from the HLA genetic profile of the individual. We use ethnicity-specific HLA class-I allele frequency data, together with genome sequences of various H1N1 viral strains, to obtain susceptibility sub-populations for 61 ethnicities and 81 viral strains isolated in 2009, as well as 85 strains isolated in other years. We incorporate these data into a multi-compartment SIR model to analyse the epidemic dynamics for these (ethnicity, viral strain) epidemic pairs. Our results show that HLA allele profiles which lead to a large spread in individual susceptibility values can act as a protective barrier against the spread of influenza. We predict that populations skewed such that a small number of highly susceptible individuals coexist with a large number of less susceptible ones, should exhibit smaller outbreaks than populations with the same average susceptibility but distributed more uniformly across individuals. Our model tracks some well-known qualitative trends of influenza spread worldwide, suggesting that HLA genetic diversity plays a crucial role in determining the spreading potential of different influenza viral strains across populations.