Tularemia Outbreak Investigation in Kosovo: Case Control and Environmental Studies

A large outbreak of tularemia occurred in Kosovo in the early postwar period, 1999-2000. Epidemiologic and environmental investigations were conducted to identify sources of infection, modes of transmission, and household risk factors. Case and control status was verified by enzyme-linked immunosorbent assay, Western blot, and microagglutination assay. A total of 327 serologically confirmed cases of tularemia pharyngitis and cervical lymphadenitis were identified in 21 of 29 Kosovo municipalities. Matched analysis of 46 case households and 76 control households suggested that infection was transmitted through contaminated food or water and that the source of infection was rodents. Environmental circumstances in war-torn Kosovo led to epizootic rodent tularemia and its spread to resettled rural populations living under circumstances of substandard housing, hygiene, and sanitation

An ancestry informative marker set for determining continental origin: validation and extension using human genome diversity panels

<p>Abstract</p> <p>Background</p> <p>Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia.</p> <p>Results</p> <p>In this study, genotypes from Human Genome Diversity Panel populations were used to further evaluate a 93 SNP AIM panel, a subset of the 128 AIMS set, for distinguishing continental origins. Using both model-based and relatively model-independent methods, we here confirm the ability of this AIM set to distinguish diverse population groups that were not previously evaluated. This study included multiple population groups from Oceana, South Asia, East Asia, Sub-Saharan Africa, North and South America, and Europe. In addition, the 93 AIM set provides population substructure information that can, for example, distinguish Arab and Ashkenazi from Northern European population groups and Pygmy from other Sub-Saharan African population groups.</p> <p>Conclusion</p> <p>These data provide additional support for using the 93 AIM set to efficiently identify continental subject groups for genetic studies, to identify study population outliers, and to control for admixture in association studies.</p

Analysis of East Asia Genetic Substructure Using Genome-Wide SNP Arrays

Accounting for population genetic substructure is important in reducing type 1 errors in genetic studies of complex disease. As efforts to understand complex genetic disease are expanded to different continental populations the understanding of genetic substructure within these continents will be useful in design and execution of association tests. In this study, population differentiation (Fst) and Principal Components Analyses (PCA) are examined using >200 K genotypes from multiple populations of East Asian ancestry. The population groups included those from the Human Genome Diversity Panel [Cambodian, Yi, Daur, Mongolian, Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, Xibo, and Yakut], HapMap [ Han Chinese (CHB) and Japanese (JPT)], and East Asian or East Asian American subjects of Vietnamese, Korean, Filipino and Chinese ancestry. Paired Fst (Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups (CHB/Korean, 0.0019; CHB/JPT, 00651; CHB/Vietnamese, 0.0065) with larger separation with Filipino (CHB/Filipino, 0.014). Low levels of differentiation were also observed between Dai and Vietnamese (0.0045) and between Vietnamese and Cambodian (0.0062). Similarly, small Fst's were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan (Fst's <0.0025 with CHB). For PCA, the first two PC's showed a pattern of relationships that closely followed the geographic distribution of the different East Asian populations. PCA showed substructure both between different East Asian groups and within the Han Chinese population. These studies have also identified a subset of East Asian substructure ancestry informative markers (EASTASAIMS) that may be useful for future complex genetic disease association studies in reducing type 1 errors and in identifying homogeneous groups that may increase the power of such studies

Genomic changes associated with the evolutionary transition of an insect gut symbiont into a blood-borne pathogen.

The genus Bartonella comprises facultative intracellular bacteria with a unique lifestyle. After transmission by blood-sucking arthropods they colonize the erythrocytes of mammalian hosts causing acute and chronic infectious diseases. Although the pathogen-host interaction is well understood, little is known about the evolutionary origin of the infection strategy manifested by Bartonella species. Here we analyzed six genomes of Bartonella apis, a honey bee gut symbiont that to date represents the closest relative of pathogenic Bartonella species. Comparative genomics revealed that B. apis encodes a large set of vertically inherited genes for amino acid and cofactor biosynthesis and nitrogen metabolism. Most pathogenic bartonellae have lost these ancestral functions, but acquired specific virulence factors and expanded a vertically inherited gene family for harvesting cofactors from the blood. However, the deeply rooted pathogen Bartonella tamiae has retained many of the ancestral genome characteristics reflecting an evolutionary intermediate state toward a host-restricted intraerythrocytic lifestyle. Our findings suggest that the ancestor of the pathogen Bartonella was a gut symbiont of insects and that the adaptation to blood-feeding insects facilitated colonization of the mammalian bloodstream. This study highlights the importance of comparative genomics among pathogens and non-pathogenic relatives to understand disease emergence within an evolutionary-ecological framework

First Reported Prairie Dog–to-Human Tularemia Transmission, Texas, 2002

A tularemia outbreak, caused by Francisella tularensis type B, occurred among wild-caught, commercially traded prairie dogs. F. tularensis microagglutination titers in one exposed person indicated recent infection. These findings represent the first evidence for prairie-dog-to-human tularemia transmission and demonstrate potential human health risks of the exotic pet trade

High-Density SNP Screening of the Major Histocompatibility Complex in Systemic Lupus Erythematosus Demonstrates Strong Evidence for Independent Susceptibility Regions

A substantial genetic contribution to systemic lupus erythematosus (SLE) risk is conferred by major histocompatibility complex (MHC) gene(s) on chromosome 6p21. Previous studies in SLE have lacked statistical power and genetic resolution to fully define MHC influences. We characterized 1,610 Caucasian SLE cases and 1,470 parents for 1,974 MHC SNPs, the highly polymorphic HLA-DRB1 locus, and a panel of ancestry informative markers. Single-marker analyses revealed strong signals for SNPs within several MHC regions, as well as with HLA-DRB1 (global p = 9.99×10−16). The most strongly associated DRB1 alleles were: *0301 (odds ratio, OR = 2.21, p = 2.53×10−12), *1401 (OR = 0.50, p = 0.0002), and *1501 (OR = 1.39, p = 0.0032). The MHC region SNP demonstrating the strongest evidence of association with SLE was rs3117103, with OR = 2.44 and p = 2.80×10−13. Conditional haplotype and stepwise logistic regression analyses identified strong evidence for association between SLE and the extended class I, class I, class III, class II, and the extended class II MHC regions. Sequential removal of SLE–associated DRB1 haplotypes revealed independent effects due to variation within OR2H2 (extended class I, rs362521, p = 0.006), CREBL1 (class III, rs8283, p = 0.01), and DQB2 (class II, rs7769979, p = 0.003, and rs10947345, p = 0.0004). Further, conditional haplotype analyses demonstrated that variation within MICB (class I, rs3828903, p = 0.006) also contributes to SLE risk independent of HLA-DRB1*0301. Our results for the first time delineate with high resolution several MHC regions with independent contributions to SLE risk. We provide a list of candidate variants based on biologic and functional considerations that may be causally related to SLE risk and warrant further investigation

A Genome-Wide Association Scan on the Levels of Markers of Inflammation in Sardinians Reveals Associations That Underpin Its Complex Regulation

Identifying the genes that influence levels of pro-inflammatory molecules can help to elucidate the mechanisms underlying this process. We first conducted a two-stage genome-wide association scan (GWAS) for the key inflammatory biomarkers Interleukin-6 (IL-6), the general measure of inflammation erythrocyte sedimentation rate (ESR), monocyte chemotactic protein-1 (MCP-1), and high-sensitivity C-reactive protein (hsCRP) in a large cohort of individuals from the founder population of Sardinia. By analysing 731,213 autosomal or X chromosome SNPs and an additional ∼1.9 million imputed variants in 4,694 individuals, we identified several SNPs associated with the selected quantitative trait loci (QTLs) and replicated all the top signals in an independent sample of 1,392 individuals from the same population. Next, to increase power to detect and resolve associations, we further genotyped the whole cohort (6,145 individuals) for 293,875 variants included on the ImmunoChip and MetaboChip custom arrays. Overall, our combined approach led to the identification of 9 genome-wide significant novel independent signals—5 of which were identified only with the custom arrays—and provided confirmatory evidence for an additional 7. Novel signals include: for IL-6, in the ABO gene (rs657152, p = 2.13×10−29); for ESR, at the HBB (rs4910472, p = 2.31×10−11) and UCN119B/SPPL3 (rs11829037, p = 8.91×10−10) loci; for MCP-1, near its receptor CCR2 (rs17141006, p = 7.53×10−13) and in CADM3 (rs3026968, p = 7.63×10−13); for hsCRP, within the CRP gene (rs3093077, p = 5.73×10−21), near DARC (rs3845624, p = 1.43×10−10), UNC119B/SPPL3 (rs11829037, p = 1.50×10−14), and ICOSLG/AIRE (rs113459440, p = 1.54×10−08) loci. Confirmatory evidence was found for IL-6 in the IL-6R gene (rs4129267); for ESR at CR1 (rs12567990) and TMEM57 (rs10903129); for MCP-1 at DARC (rs12075); and for hsCRP at CRP (rs1205), HNF1A (rs225918), and APOC-I (rs4420638). Our results improve the current knowledge of genetic variants underlying inflammation and provide novel clues for the understanding of the molecular mechanisms regulating this complex process

Population- and individual-specific regulatory variation in Sardinia

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.M.P. is supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement 633964 (ImmunoAgeing). Z.Z. is supported by the National Science Foundation (NSF) GRFP (DGE- 114747) and by the Stanford Center for Computational, Evolutionary, and Human Genomics (CEHG). Z.Z., J.R.D., and G.T.H. also acknowledge support from the Stanford Genome Training Program (SGTP; NIH/NHGRI T32HG000044). J.R.D. is supported by the Stanford Graduate Fellowship. K.R.K. is supported by Department of Defense, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEQ) Fellowship 32 CFR 168a. S.J.S. is supported by the NIHR Cambridge Biomedical Research Centre. The SardiNIA project is supported in part by the intramural program of the National Institute on Aging through contract HHSN271201100005C to the Consiglio Nazionale delle Ricerche of Italy. The RNA sequencing was supported by the PB05 InterOmics MIUR Flagship grant; by the FaReBio2011 “Farmaci e Reti Biotecnologiche di Qualità” grant; and by Sardinian Autonomous Region (L.R. no. 7/2009) grant cRP3-154 to F. Cucca, who is also supported by the Italian Foundation for Multiple Sclerosis (FISM 2015/R/09) and by the Fondazione di Sardegna (ex Fondazione Banco di Sardegna, Prot. U1301.2015/AI.1157.BE Prat. 2015-1651). S.B.M. is supported by the US National Institutes of Health through R01HG008150, R01MH101814, U01HG007436, and U01HG009080. All of the authors would like to thank the CRS4 and the SCGPM for the computational infrastructure supporting this project