• Inherited ciHHV-6 was detected in 1.4% of HCT recipients and 0.9% of their donors.• Acute GVHD grades 2-4 and cytomegalovirus viremia were more frequent when recipients or donors had inherited ciHHV-6.Human herpesvirus 6 (HHV-6) species have a unique ability to integrate into chromosomal telomeres. Mendelian inheritance via gametocyte integration results in HHV-6 in every nucleated cell. The epidemiology and clinical effect of inherited chromosomally integrated HHV-6 (iciHHV-6) in hematopoietic cell transplant (HCT) recipients is unclear.We identified 4319 HCT donor-recipient pairs (8638 subjects) who received an allogeneic HCT and had archived pre-HCT peripheral blood mononuclear cell samples. We screened these samples for iciHHV-6 and compared characteristics of HCT recipients and donors with iciHHV-6 with those of recipients and donors without iciHHV-6, respectively. We calculated Kaplan-Meier probability estimates and Cox proportional hazards models for post-HCT outcomes based on recipient and donor iciHHV-6 status. We identified 60 HCT recipients (1.4%) and 40 donors (0.9%) with iciHHV-6; both recipient and donor harbored iciHHV-6 in 13 HCTs. Thus, there were 87 HCTs (2%) in which the recipient, donor, or both harbored iciHHV-6. Acute graft-versus-host disease (GVHD) grades 2-4 was more frequent when recipients or donors had iciHHV-6 (adjusted hazard ratios, 1.7-1.9; P 5 .004-.001). Cytomegalovirus viremia (any and high-level) was more frequent among recipients with iciHHV-6 (adjusted HRs, 1.7-3.1; P 5 .001-.040). Inherited ciHHV-6 status did not significantly affect risk for chronic GVHD, hematopoietic cell engraftment, overall mortality, or nonrelapse mortality. Screening for iciHHV-6 could guide donor selection and post-HCT risk stratification and treatment. Further study is needed to replicate these findings and identify potential mechanisms. (Blood. 2017;130(8):1062-1069

No abstract

The genetic control of gene expression is a core component of human physiology. For the past several years, transcriptome-wide association studies have leveraged large datasets of linked genotype and RNA sequencing information to create a powerful gene-based test of association that has been used in dozens of studies. While numerous discoveries have been made, the populations in the training data are overwhelmingly of European descent, and little is known about the generalizability of these models to other populations. Here, we test for cross-population generalizability of gene expression prediction models using a dataset of African American individuals with RNA-Seq data in whole blood. We find that the default models trained in large datasets such as GTEx and DGN fare poorly in African Americans, with a notable reduction in prediction accuracy when compared to European Americans. We replicate these limitations in cross-population generalizability using the five populations in the GEUVADIS dataset. Via realistic simulations of both populations and gene expression, we show that accurate cross-population generalizability of transcriptome prediction only arises when eQTL architecture is substantially shared across populations. In contrast, models with non-identical eQTLs showed patterns similar to real-world data. Therefore, generating RNA-Seq data in diverse populations is a critical step towards multiethnic utility of gene expression prediction.

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods have focused only on individuals with one primary continental ancestry, thus poorly accommodating recently-admixed individuals. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals by explicitly modeling ancestry-specific effects and jointly estimating ancestry-shared effects. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses.