Alzheimer disease susceptibility loci: evidence for a protein network under natural selection.

Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences Department of Neurology, Brigham and Women's Hospital, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
The American Journal of Human Genetics (Impact Factor: 10.99). 04/2012; 90(4):720-6. DOI: 10.1016/j.ajhg.2012.02.022
Source: PubMed

ABSTRACT Recent genome-wide association studies have identified a number of susceptibility loci for Alzheimer disease (AD). To understand the functional consequences and potential interactions of the associated loci, we explored large-scale data sets interrogating the human genome for evidence of positive natural selection. Our findings provide significant evidence for signatures of recent positive selection acting on several haplotypes carrying AD susceptibility alleles; interestingly, the genes found in these selected haplotypes can be assembled, independently, into a molecular complex via a protein-protein interaction (PPI) network approach. These results suggest a possible coevolution of genes encoding physically-interacting proteins that underlie AD susceptibility and are coexpressed in different tissues. In particular, PICALM, BIN1, CD2AP, and EPHA1 are interconnected through multiple interacting proteins and appear to have coordinated evidence of selection in the same human population, suggesting that they may be involved in the execution of a shared molecular function. This observation may be AD-specific, as the 12 loci associated with Parkinson disease do not demonstrate excess evidence of natural selection. The context for selection is probably unrelated to AD itself; it is likely that these genes interact in another context, such as in immune cells, where we observe cis-regulatory effects at several of the selected AD loci.


Available from: Barbara E Stranger, May 09, 2015
1 Follower
  • [Show abstract] [Hide abstract]
    ABSTRACT: The protein product of the MX2 (myxovirus resistance 2) gene restricts HIV-1 and simian retroviruses. We demonstrate that MX2 evolved adaptively in mammals with distinct sites representing selection targets in distinct branches; selection mainly involved residues in loop 4, previously shown to carry antiviral determinants. Modeling data indicated that positively selected sites form a continuous surface on loop 4, which folds into two antiparallel α-helices protruding from the stalk domain. A population genetics-phylogenetics approach indicated that the coding region of MX2 mainly evolved under negative selection in the human lineage. Nonetheless, population genetic analyses demonstrated that natural selection operated on MX2 during the recent history of human populations: distinct selective events drove the frequency increase of two haplotypes in populations of Asian and European ancestry. The Asian haplotype carries a susceptibility allele for melanoma; the European haplotype is tagged by rs2074560, an intronic variant. Analyses performed on three independent European cohorts of HIV-1 exposed seronegative individuals with different geographic origin and distinct exposure route showed that the ancestral (G) allele of rs2074560 protects from HIV-1 infection with a recessive effect (combined p value = 1.55×10(-4)). The same allele is associated with lower in vitro HIV-1 replication and increases MX2 expression levels in response to IFN-α. Data herein exploit evolutionary information to identify a novel host determinant of HIV-1 infection susceptibility.
    Molecular Biology and Evolution 06/2014; 31(9). DOI:10.1093/molbev/msu193 · 14.31 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Ovarian cancer is a deadly female reproductive cancer. Understanding the biological mechanisms underlying ovarian cancer could help lead to quicker and more accurate diagnosis and more effective treatments. Both changes in microRNA(miRNA) expression and miRNA/mRNA dysregulation have been associated with ovarian cancer. With the availability of whole-genome miRNA and mRNA sequencing we now have new potentials to study these associations. In this study, we performed a comprehensive analysis of miRNA and mRNA expression in ovarian cancer using an integrative network approach combined with association analysis. We developed an integrative approach to construct a network that illustrates the complex interplay among miRNA and gene expression from a systems perspective. Our method is composed of expanding networks from eQTL associations, building network associations in eQTL analysis, and then combine the networks into an integrated network. This integrated network takes account of miRNA expression quantitative trait loci (eQTL) associations, miRNAs and their targets, protein-protein interactions, co-expressions among miRNAs and genes respectively. Applied to the ovarian cancer data set from The Cancer Genome Atlas (TCGA), we created an integrated network with 167 nodes containing 108 miRNA-target interactions and 145 from protein-protein interactions, starting from 44 initial eQTLs. This integrated network encompassed 26 genes and 14 miRNAs associated with cancer. In particular, 11 genes and 12 miRNAs in the integrated network are associated with ovarian cancer. We demonstrated an integrated network approach that integrates multiple data sources at a systems level. We applied this approach to the TCGA ovarian cancer dataset, and constructed a network that provided a more inclusive view of miRNA and gene expression in ovarian cancer. This network included four separate types of interactions among miRNAs and genes. Simply analyzing each interaction component in isolation, such as the eQTL associations, the miRNA-target interactions or the protein-protein interactions, would create a much more limited network than the integrated one.
    BMC Bioinformatics 03/2015; 16(Suppl 5):S5. DOI:10.1186/1471-2105-16-S5-S5 · 2.67 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: We used a collection of 708 prospectively collected autopsied brains to assess the methylation state of the brain's DNA in relation to Alzheimer's disease (AD). We found that the level of methylation at 71 of the 415,848 interrogated CpGs was significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validated 11 of the differentially methylated regions in an independent set of 117 subjects. Furthermore, we functionally validated these CpG associations and identified the nearby genes whose RNA expression was altered in AD: ANK1, CDH23, DIP2A, RHBDF2, RPL13, SERPINF1 and SERPINF2. Our analyses suggest that these DNA methylation changes may have a role in the onset of AD given that we observed them in presymptomatic subjects and that six of the validated genes connect to a known AD susceptibility gene network.
    Nature Neuroscience 08/2014; 17(9). DOI:10.1038/nn.3786 · 14.98 Impact Factor