The association between single-nucleotide polymorphisms within type 1 interferon pathway genes and human immunodeficiency virus type 1 viral load in antiretroviral-naïve participants.

BACKGROUND: Human genetic contribution to HIV progression remains inadequately explained. The type 1 interferon (IFN) pathway is important for host control of HIV and variation in type 1 IFN genes may contribute to disease progression. This study assessed the impact of variations at the gene and pathway level of type 1 IFN on HIV-1 viral load (VL). METHODS: Two cohorts of antiretroviral (ART) naïve participants living with HIV (PLWH) with either early (START) or advanced infection (FIRST) were analysed separately. Type 1 IFN genes (n = 17) and receptor subunits (IFNAR1, IFNAR2) were examined for both cumulated type 1 IFN pathway analysis and individual gene analysis. SKAT-O was applied to detect associations between the genotype and HIV-1 study entry viral load (log10 transformed) as a proxy for set point VL; P-values were corrected using Bonferroni (P < 0.0025). RESULTS: The analyses among those with early infection included 2429 individuals from five continents. The median study entry HIV VL was 14,623 (IQR 3460-45100) copies/mL. Across 673 SNPs within 19 type 1 IFN genes, no significant association with study entry VL was detected. Conversely, examining individual genes in START showed a borderline significant association between IFNW1, and study entry VL (P = 0.0025). This significance remained after separate adjustments for age, CD4+ T-cell count, CD4+/CD8+ T-cell ratio and recent infection. When controlling for population structure using linear mixed effects models (LME), in addition to principal components used in the main model, this was no longer significant (p = 0.0244). In subgroup analyses stratified by geographical region, the association between IFNW1 and study entry VL was only observed among African participants, although, the association was not significant when controlling for population structure using LME. Of the 17 SNPs within the IFNW1 region, only rs79876898 (A > G) was associated with study entry VL (p = 0.0020, beta = 0.32; G associated with higher study entry VL than A) in single SNP association analyses. The findings were not reproduced in FIRST participants. CONCLUSION: Across 19 type 1 IFN genes, only IFNW1 was associated with HIV-1 study entry VL in a cohort of ART-naïve individuals in early stages of their infection, however, this was no longer significant in sensitivity analyses that controlled for population structures using LME.

Predicting type 2 diabetes risk before and after solid organ transplantation using polygenic scores in a Danish cohort.

Type 2 diabetes mellitus (T2DM) can be multifactorial where both genetics and environmental factors play a role. We aimed to investigate the use of polygenic risk scores (PRS) in the prediction of pre-transplant T2DM and post-transplant diabetes mellitus (PTDM) among solid organ transplant (SOT) patients. Using non-genetic risk scores alone; and the combination with PRS, separate logistic regression models were built and compared using receiver operator curves. Patients were assessed pre-transplant and in three post-transplant periods: 0-45, 46-365 and >365 days. A higher PRS was significantly associated with increased odds of pre-transplant T2DM. However, no improvement was observed for pre-transplant T2DM prediction when comparing PRS combined with non-genetic risk scores to using non-genetic risk scores alone. This was also true for predictions of PTDM in all three post-transplant periods. This study demonstrated that polygenic risk was only associated with the risk of T2DM among SOT recipients prior to transplant and not for PTDM. Combining PRS with a clinical model of non-genetic risk scores did not significantly improve the predictive ability, indicating its limited clinical utility in identifying patients at high risk for T2DM before transplantation, suggesting that non-genetic or different genetic factors may contribute to PTDM.

Associations of functional human leucocyte antigen class I groups with HIV viral load in a heterogeneous cohort.

OBJECTIVE: Human leucocyte antigen (HLA) class I alleles are the main host genetic factors involved in controlling HIV-1 viral load (VL). Nevertheless, HLA diversity has proven a significant challenge in association studies. We assessed how accounting for binding affinities of HLA class I alleles to HIV-1 peptides facilitate association testing of HLA with HIV-1 VL in a heterogeneous cohort. DESIGN: Cohort from the Strategic Timing of AntiRetroviral Treatment (START) study. METHODS: We imputed HLA class I alleles from host genetic data (2546 HIV+ participants) and sampled immunopeptidomes from 2079 host-paired viral genomes (targeted amplicon sequencing). We predicted HLA class I binding affinities to HIV-1 and unspecific peptides, grouping alleles into functional clusters through consensus clustering. These functional HLA class I clusters were used to test associations with HIV VL. RESULTS: We identified four clades totaling 30 HLA alleles accounting for 11.4% variability in VL. We highlight HLA-B∗57:01 and B∗57:03 as functionally similar but yet overrepresented in distinct ethnic groups, showing when combined a protective association with HIV+ VL (log, ß -0.25; adj. P-value < 0.05). We further demonstrate only a slight power reduction when using unspecific immunopeptidomes, facilitating the use of the inferred functional HLA groups in other studies. CONCLUSION: The outlined computational approach provides a robust and efficient way to incorporate HLA function and peptide diversity, aiding clinical association studies in heterogeneous cohorts. To facilitate access to the proposed methods and results we provide an interactive application for exploring data.

Association between ten-eleven methylcytosine dioxygenase 2 genetic variation and viral load in people with HIV.

INTRODUCTION: Identifying genetic factors that influence HIV-pathogenesis is critical for understanding disease pathways. Previous studies have suggested a role for the human gene ten-eleven methylcytosine dioxygenase 2 (TET2) in modulating HIV-pathogenesis. METHODS: We assessed whether genetic variation in TET2 was associated with markers of HIV-pathogenesis using both gene level and single nucleotide polymorphism (SNP) level association in 8512 HIV-positive persons across five clinical trial cohorts. RESULTS: Variation at both the gene and SNP-level of TET2 was found to be associated with levels of HIV viral load (HIV-VL) consistently in the two cohorts that recruited antiretroviral-naïve participants. The SNPs occurred in two clusters of high linkage disequilibrium (LD), one associated with high HIV-VL and the other low HIV-VL, and were predominantly found in Black participants. CONCLUSION: Genetic variation in TET2 was associated with HIV-VL in two large antiretroviral therapy (ART)-naive clinical trial cohorts. The role of TET2 in HIV-pathogenesis warrants further investigation.

The association of human leukocyte antigen alleles with clinical disease progression in HIV-positive cohorts with varied treatment strategies.

OBJECTIVES: The Strategic Timing of AntiRetroviral Treatment (START) and Strategies for Management of Antiretroviral Therapy (SMART) trials demonstrated that ART can partly reverse clinically defined immune dysfunction induced by HIV replication. As control of HIV replication is influenced by the HLA region, we explored whether HLA alleles independently influence the risk of clinical events in HIV+ individuals. DESIGN: Cohort study. METHODS: In START and SMART participants, associations between imputed HLA alleles and AIDS, infection-related cancer, herpes virus-related AIDS events, chronic inflammation-related conditions, and bacterial pneumonia were assessed. Cox regression was used to estimate hazard ratios for the risk of events among allele carriers versus noncarriers. Models were adjusted for sex, age, geography, race, time-updated CD4+ T-cell counts and HIV viral load and stratified by treatment group within trials. HLA class I and II alleles were analyzed separately. The Benjamini--Hochberg procedure was used to limit the false discovery rate to less than 5% (i.e. q value <0.05). RESULTS: Among 4829 participants, there were 132 AIDS events, 136 chronic inflammation-related conditions, 167 bacterial pneumonias, 45 infection-related cancers, and 49 herpes virus-related AIDS events. Several associations with q value less than 0.05 were found: HLA-DQB1∗06:04 and HLA-DRB1∗13:02 with AIDS (adjusted HR [95% CI] 2.63 [1.5-4.6] and 2.25 [1.4-3.7], respectively), HLA-B∗15:17 and HLA-DPB1∗15:01 with bacterial pneumonia (4.93 [2.3-10.7] and 4.33 [2.0-9.3], respectively), and HLA-A∗69:01 with infection-related cancer (15.26 [3.5-66.7]). The carriage frequencies of these alleles were 10% or less. CONCLUSION: This hypothesis-generating study suggests that certain HLA alleles may influence the risk of immune dysfunction-related events irrespective of viral load and CD4+ T-cell count.

Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges.

The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8+ T cells for age and CD4+ T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans-specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes.

An ApiAP2 member regulates expression of clonally variant genes of the human malaria parasite Plasmodium falciparum.

Variegated surface antigen expression is key to chronic infection and pathogenesis of the human malaria parasite Plasmodium falciparum. This protozoan parasite expresses distinct surface molecules that are encoded by clonally variant gene families such as var, rif and stevor. The molecular mechanisms governing activation of individual members remain ill-defined. To investigate the molecular events of the initial transcriptional activation process we focused on a member of the apicomplexan ApiAP2 transcription factor family predicted to bind to the 5' upstream regions of the var gene family, AP2-exp (PF3D7_1466400). Viable AP2-exp mutant parasites rely on expressing no less than a short truncated protein including the N-terminal AP2 DNA-binding domain. RNA-seq analysis in mutant parasites revealed transcriptional changes in a subset of exported proteins encoded by clonally variant gene families. Upregulation of RIFINs and STEVORs was validated at the protein levels. In addition, morphological alterations were observed on the surface of the host cells infected by the mutants. This work points to a complex regulatory network of clonally variant gene families in which transcription of a subset of members is regulated by the same transcription factor. In addition, we highlight the importance of the non-DNA binding AP2 domain in functional gene regulation.

In Silico discovery of transcription factors as potential diagnostic biomarkers of ovarian cancer.

BACKGROUND: Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC) through the study of transcription regulation of genes affected by estrogen hormone. RESULTS: The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs) that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers. CONCLUSIONS: We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors.

dPORE-miRNA: polymorphic regulation of microRNA genes.

BACKGROUND: MicroRNAs (miRNAs) are short non-coding RNA molecules that act as post-transcriptional regulators and affect the regulation of protein-coding genes. Mostly transcribed by PolII, miRNA genes are regulated at the transcriptional level similarly to protein-coding genes. In this study we focus on human miRNAs. These miRNAs are involved in a variety of pathways and can affect many diseases. Our interest is on possible deregulation of the transcription initiation of the miRNA encoding genes, which is facilitated by variations in the genomic sequence of transcriptional control regions (promoters). METHODOLOGY: Our aim is to provide an online resource to facilitate the investigation of the potential effects of single nucleotide polymorphisms (SNPs) on miRNA gene regulation. We analyzed SNPs overlapped with predicted transcription factor binding sites (TFBSs) in promoters of miRNA genes. We also accounted for the creation of novel TFBSs due to polymorphisms not present in the reference genome. The resulting changes in the original TFBSs and potential creation of new TFBSs were incorporated into the Dragon Database of Polymorphic Regulation of miRNA genes (dPORE-miRNA). CONCLUSIONS: The dPORE-miRNA database enables researchers to explore potential effects of SNPs on the regulation of miRNAs. dPORE-miRNA can be interrogated with regards to: a/miRNAs (their targets, or involvement in diseases, or biological pathways), b/SNPs, or c/transcription factors. dPORE-miRNA can be accessed at http://cbrc.kaust.edu.sa/dpore and http://apps.sanbi.ac.za/dpore/. Its use is free for academic and non-profit users.

Deciphering the transcriptional circuitry of microRNA genes expressed during human monocytic differentiation.

BACKGROUND: Macrophages are immune cells involved in various biological processes including host defence, homeostasis, differentiation, and organogenesis. Disruption of macrophage biology has been linked to increased pathogen infection, inflammation and malignant diseases. Differential gene expression observed in monocytic differentiation is primarily regulated by interacting transcription factors (TFs). Current research suggests that microRNAs (miRNAs) degrade and repress translation of mRNA, but also may target genes involved in differentiation. We focus on getting insights into the transcriptional circuitry regulating miRNA genes expressed during monocytic differentiation. RESULTS: We computationally analysed the transcriptional circuitry of miRNA genes during monocytic differentiation using in vitro time-course expression data for TFs and miRNAs. A set of TF-->miRNA associations was derived from predicted TF binding sites in promoter regions of miRNA genes. Time-lagged expression correlation analysis was utilised to evaluate the TF-->miRNA associations. Our analysis identified 12 TFs that potentially play a central role in regulating miRNAs throughout the differentiation process. Six of these 12 TFs (ATF2, E2F3, HOXA4, NFE2L1, SP3, and YY1) have not previously been described to be important for monocytic differentiation. The remaining six TFs are CEBPB, CREB1, ELK1, NFE2L2, RUNX1, and USF2. For several miRNAs (miR-21, miR-155, miR-424, and miR-17-92), we show how their inferred transcriptional regulation impacts monocytic differentiation. CONCLUSIONS: The study demonstrates that miRNAs and their transcriptional regulatory control are integral molecular mechanisms during differentiation. Furthermore, it is the first study to decipher on a large-scale, how miRNAs are controlled by TFs during human monocytic differentiation. Subsequently, we have identified 12 candidate key controllers of miRNAs during this differentiation process.

Genomic anatomy of the hippocampus.

Availability of genome-scale in situ hybridization data allows systematic analysis of genetic neuroanatomical architecture. Within the hippocampus, electrophysiology and lesion and imaging studies demonstrate functional heterogeneity along the septotemporal axis, although precise underlying circuitry and molecular substrates remain uncharacterized. Application of unbiased statistical component analyses to genome-scale hippocampal gene expression data revealed robust septotemporal molecular heterogeneity, leading to the identification of a large cohort of genes with robust regionalized hippocampal expression. Manual mapping of heterogeneous CA3 pyramidal neuron expression patterns demonstrates an unexpectedly complex molecular parcellation into a relatively coherent set of nine expression domains in the septal/temporal and proximal/distal axes with reciprocal, nonoverlapping boundaries. Unique combinatorial profiles of adhesion molecules within these domains suggest corresponding differential connectivity, which is demonstrated for CA3 projections to the lateral septum using retrograde labeling. This complex, discrete molecular architecture provides a novel paradigm for predicting functional differentiation across the full septotemporal extent of the hippocampus.

Prioritizing genes of potential relevance to diseases affected by sex hormones: an example of myasthenia gravis.

BACKGROUND: About 5% of western populations are afflicted by autoimmune diseases many of which are affected by sex hormones. Autoimmune diseases are complex and involve many genes. Identifying these disease-associated genes contributes to development of more effective therapies. Also, association studies frequently imply genomic regions that contain disease-associated genes but fall short of pinpointing these genes. The identification of disease-associated genes has always been challenging and to date there is no universal and effective method developed. RESULTS: We have developed a method to prioritize disease-associated genes for diseases affected strongly by sex hormones. Our method uses various types of information available for the genes, but no information that directly links genes with the disease. It generates a score for each of the considered genes and ranks genes based on that score. We illustrate our method on early-onset myasthenia gravis (MG) using genes potentially controlled by estrogen and localized in a genomic segment (which contains the MHC and surrounding region) strongly associated with MG. Based on the considered genomic segment 283 genes are ranked for their relevance to MG and responsiveness to estrogen. The top three ranked genes, HLA-G, TAP2 and HLA-DRB1, are implicated in autoimmune diseases, while TAP2 is associated with SNPs characteristic for MG. Within the top 35 prioritized genes our method identifies 90% of the 10 already known MG-associated genes from the considered region without using any information that directly links genes to MG. Among the top eight genes we identified HLA-G and TUBB as new candidates. We show that our ab-initio approach outperforms the other methods for prioritizing disease-associated genes. CONCLUSION: We have developed a method to prioritize disease-associated genes under the potential control of sex hormones. We demonstrate the success of this method by prioritizing the genes localized in the MHC and surrounding region and evaluating the role of these genes as potential candidates for estrogen control as well as MG. We show that our method outperforms the other methods. The method has a potential to be adapted to prioritize genes relevant to other diseases.