title: A whole genome association study of mother-to-child transmission of HIV in Malawi.
abstract: BACKGROUND
  More than 300,000 children are newly infected with HIV each year, predominantly through mother-to-child transmission (HIV MTCT). Identification of host genetic traits associated with transmission may more clearly explain the mechanisms of HIV MTCT and further the development of a vaccine to protect infants from infection. Associations between transmission and a selection of genes or single nucleotide polymorphisms (SNP)s may give an incomplete picture of HIV MTCT etiology. Thus, this study employed a genome-wide association approach to identify novel variants associated with HIV MTCT.
  
  
  METHODS
  We conducted a nested case-control study of HIV MTCT using infants of HIV(+) mothers, drawn from a cohort study of malaria and HIV in pregnancy in Blantyre, Malawi. Whole genome scans (650,000 SNPs genotyped using Illumina genotyping assays) were obtained for each infant. Logistic regression was used to evaluate the association between each SNP and HIV MTCT.
  
  
  RESULTS
  Genotype results were available for 100 HIV(+) infants (at birth, 6, or 12 weeks) and 126 HIV(-) infants (at birth, 6, and 12 weeks). We identified 9 SNPs within 6 genes with a P-value < 5 × 10(-5) associated with the risk of transmission, in either unadjusted or adjusted by maternal HIV viral load analyses. Carriers of the rs8069770 variant allele were associated with a lower risk of HIV MTCT (odds ratio = 0.27, 95% confidence interval = 0.14, 0.51), where rs8069770 is located within HS3ST3A1, a gene involved in heparan sulfate biosynthesis. Interesting associations for SNPs located within or near genes involved in pregnancy and development, innate immunological response, or HIV protein interactions were also observed.
  
  
  CONCLUSIONS
  This study used a genome-wide approach to identify novel variants associated with the risk of HIV MTCT in order to gain new insights into HIV MTCT etiology. Replication of this work using a larger sample size will help us to differentiate true positive findings.
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Bonnie R
authors.initials: BR
authors.lastname: Joubert
authors.affiliation: Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA ; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA ; Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Ethan M
authors.initials: EM
authors.lastname: Lange
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Nora
authors.initials: N
authors.lastname: Franceschini
authors.affiliation: College of Medicine, University of Malawi, Blantyre, Malawi.
authors.forename: Victor
authors.initials: V
authors.lastname: Mwapasa
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA ; Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Kari E
authors.initials: KE
authors.lastname: North
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Steven R
authors.initials: SR
authors.lastname: Meshnick