DOI: 10.5061/dryad.k3j9kd5dw
title: A cohort-based study of host gene expression: tumor suppressor and innate immune/inflammatory pathways associated with the HIV reservoir size

description: The major barrier to an HIV cure is the HIV reservoir: latently-infected
 cells that persist despite effective antiretroviral therapy (ART). Most
 prior studies of host genetic predictors of HIV control have focused on
 “elite controllers,” rare individuals able to control virus in the absence
 of ART. However, there have been few genetic studies among ART-suppressed
 non-controllers, who make up the majority of people living with HIV
 (PLWH). We performed host RNA sequencing and HIV reservoir quantification
 (total DNA [tDNA], unspliced RNA [usRNA], intact DNA) from peripheral CD4+
 T cells from 191 HIV+ ART-suppressed non-controllers. After adjusting for
 nadir CD4+ count, timing of ART initiation, and genetic ancestry, we
 identified two host genes for which higher expression was significantly
 associated with smaller total DNA viral reservoir size, P3H3 and NBL1,
 both known tumor suppressor genes. We then identified 17 host genes for
 which lower expression was associated with higher residual transcription
 (HIV usRNA). These included novel associations with membrane channel
 (KCNJ2, GJB2), inflammasome (IL1A, CSF3, TNFAIP5, TNFAIP6, TNFAIP9, CXCL3,
 CXCL10), and innate immunity (TLR7) genes (FDR-adjusted q&lt;0.05).
 Gene set enrichment analyses further identified significant associations
 of HIV usRNA with TLR4/microbial translocation (q=0.006), IL-1/NRLP3
 inflammasome (q=0.008), and IL-10 (q=0.037) signaling. Protein validation
 assays using ELISA and multiplex cytokine assays supported these observed
 inverse host gene correlations, with P3H3, IL-10, and TNF-a protein
 associations achieving statistical significance (p&lt;0.05). Of note,
 plasma IL-10 was also significantly inversely associated with HIV DNA
 (p=0.016). HIV intact DNA was not associated with differential host gene
 expression, although this may have been due to a large number of
 undetectable values in our study. Further data are needed to validate
 these findings, including functional genomic studies, larger cohorts
 including underrepresented PLWH in research, and those including dedicated
 assays to measure the replication-competent HIV reservoir.
description: HIV+ ART-suppressed non-controllers from the UCSF SCOPE and
 Options HIV+ cohorts were included in the study.
 Cryopreserved PBMCs were enriched for CD4+ T cells (StemCell,
 Vancouver, Canada), and RNA was extracted from CD4+ T cells using the
 AllPrep Universal Kit (Qiagen, Hilden, Germany) with one aliquot set aside
 for HIV reservoir quantification and a second aliquot for host RNA
 sequencing. Host RNA sequencing was analyzed using the HTStream
 pre-processing pipeline (s4hts.github.io/htstream/) was used for removing
 PCR duplicates, adapters, N characters, PolyA/T sequences, Phix
 contaminants, and poor-quality sequences (with quality score &lt;20
 with sliding window of 10 base pairs). The quality of raw reads was
 assessed using FastQC. All samples had a per base quality score and
 sequence quality score &gt;30. RNA-seq reads were then mapped to the
 human genome (GRCh38) with a corresponding annotation file from the
 GENCODE project. Alignment and gene quantification were performed using
 the STAR alignment tool and its quantification protocol. Gene expression
 was converted to counts per million (CPM). The mean-variance trend was
 estimated to assign observational weights based on predicted variance on
 log<sub>2</sub>-counts per million
 (log<sub>2</sub>-CPM) using the Limma-Voom pipeline.
 For validation of intracellularly expressed or
 membrane-associated encoded proteins, we performed ELISA from peripheral
 CD4-enriched T cells. CD4+ T cells were isolated from PBMC by negative
 selection, using the EasySep Human CD4+ T Cell Isolation Kit (StemCell
 Technologies, Vancouver, BC, Canada), following manufacturer’s guidelines.
 The Muse Human CD4 T Cell kit (Luminex, Austin, TX) in combination with
 the Guava Muse Cell Analyzer was used to determine the concentration and
 percentages of CD4+ T cells after the isolation. To generate cellular
 lysates, purified CD4+ T cells were subjected to three cycles of
 freezing/thawing, using a dry ice (frozen CO<sub>2</sub>)
 /absolute ethanol mixture and a 37˚C water bath. Complete lysis was
 verified by trypan blue staining and microscopic analysis. Lysates were
 spun down at 1,500 g for 10 min at 4˚C (to remove cellular debris) and the
 supernatants diluted 1:5 with PBS and kept at -80˚C until the time of
 protein quantification. Total protein concentration of the CD4+ T cell
 lysates was determined using the Pierce®BCA assay (Thermo Fisher
 Scientific). The mean value obtained was 0.94 mg/ml (range: 0.66 mg/ml –
 1.18 mg/ml). Chemiluminescence or absorbance was read on a SpectraMax® iD5
 multi-mode plate reader (Molecular Devices, San Jose, CA) and reported in
 relative light units (RLU). A standard curve was constructed by plotting
 the log mean RLU reading for each standard on the y-axis against the log
 of known concentrations on the x-axis using the SoftMax Pro 7.1 software
 (Molecular Devices, San Jose, CA). Data were normalized by total protein
 concentration to accurately reflect the total population of cells (live
 and dead). Briefly, a 1:5 dilution factor (based on supernatant dilution
 with PBS at the time of CD4+ T cell isolation) was used to calculate the
 concentration in the lysate before the dilution. Each protein marker was
 then quantified using the marker-specific ELISA (again, taking into
 account the 1:5 dilution performed before cryopreservation of the
 lysates). Data normalization was performed by dividing the concentration
 of each protein in the final lysate (e.g., for P3H3 in pg/ml) by the total
 protein concentration (mg/ml). For validation of the
 several inflammatory pathway genes identified in association with HIV
 usRNA, most of the encoded proteins were secreted proteins, and thus, we
 performed high-sensitivity multiplex plasma cytokine quantification (Meso
 Scale Diagnostics). Plasma levels of IP-10 (the encoded protein for
 <em>CXCL10</em>), G-CSF (<em>GCSF</em>) and
 pentraxin 3 (<em>TNFAIP5</em>) were quantified using the
 electrochemiluminescence-based 3-plex mesoscale discovery (MSD) platform
 (U-Plex mesoscale discovery, Rockville, MA); IL-10
 (<em>IL10</em>), IL-1β (<em>IL1B</em>) and TNF-α
 (<em>TNFA</em>) were measured in a separate 3-plex S-plex
 Proinflammatory panel kit, and IL‑1α (<em>IL1A</em>) was
 quantified by a V-plex kit. In all these assays, undiluted samples were
 run in duplicate following manufacturer’s instructions, and protein
 concentrations were determined using MSD Discovery Workbench (version
 4.0.13) analysis software. The light intensities from the samples were
 interpolated using a four-parameter logistic fit (FourPL) to a standard
 curve of electrochemiluminescence generated from eight calibrators of know
 concentrations. The lower limit of detection for each marker can be found
 on the manufacturer’s website (MesoScale Diagnostics, https://www.mesoscale.com/~/media/files/handout/assaylist.pdf).
description: # A cohort-based study of host gene expression: tumor suppressor and
 innate immune/inflammatory pathways associated with the HIV reservoir size
 [https://urldefense.com/v3/**https://doi.org/10.5061/dryad.k3j9kd5dw\*5D(https:/\*doi.org/10.5061/dryad.k3j9kd5dw)**;JS8!!GuAItXPztq0!jcOMW-hmT\_tw2Yxv6qPgTDrXn851AWcX3Ij6p16kOr98gDyJo4mSMjd1x9idt5d4YSlalvnxZ423CrRR6AvdaUQh$ These data include host bulk RNA-seq data from peripheral CD4+ T cells from 191 people with HIV-infected adults, virally suppressed on antiretroviral therapy (ART). Cryopreserved PBMCs were enriched for CD4+ T cells (StemCell, Vancouver, Canada), and RNA was extracted from CD4+ T cells using the AllPrep Universal Kit (Qiagen, Hilden, Germany). For validation of intracellularly expressed or membrane-associated encoded proteins, we performed ELISA in a subset of the participants, using matched peripheral CD4-enriched T cells of 5 proteins (Kir2.1, connexin 26, P3H3, NBL1 and TLR4) encoded by KCNJ2, GJB2, P3H3, NBL1 and TLR4 respectively. For validation of the several inflammatory pathway genes, protein validation was performed in a subset of 175 participants, quantifying G-CSF, IP-10, TNFAIP5 (Pentraxin-3), IL-1b, IL-10, TNF-a, and sTLR4 expression using a high-sensitivity multiplex cytokine assay from matched plasma samples (Meso Scale Discovery)and a TLR4 ELISA kit (LSBio). ## Description of the data and file structure Participant data has been split across five `.csv` files corresponding to provenance: ELISA, plasma cytokines, intact HIV DNA ddPCR, RNAseq, and clinical covariates. De-identified participant IDs are used throughout to link the data files. The data files are described below. * `data_cd4_protein.csv` contains normalized protein expression values from the ELISAs. Each value was calculated as the ratio of the concentration of each marker (ng/ml or pg/ml) divided by the total protein concentration of the CD4+ T cell lysate(mg/ml). * `uuid`: unique participant identifier * `GJB2`: normalized protein expression data for GJB2 * `KCNJ2`: normalized protein expression data for KCNJ2 * `NBL1`: normalized protein expression data for NBL1 * `P3H3`: normalized protein expression data for P3H3 * `TLR4`: normalized protein expression data for TLR4 * `data_clinical.csv` contains clinical data for each patient in our study. * `uuid`: unique participant identifier * `gender`: one of "Male", "Female", or "Male to Female Transgender" * `age`: patient age at baseline visit (years) * `cd4_nadir_lab`: lab reported nadir CD4 value (cells/mm^3) * `newvl_preart`: pre-ART viral load (copies/mL) * `imp_eddi_arv_days`: timing of ART initiation in days (when necessary, missing values are imputed by the median of observed values greater than half a year) * `dna_copies_million`: HIV viral DNA (copies/million) * `rna_copies_million`: HIV viral RNA (copies/million) * `intact_dna.csv` contains ddPCR measurements of intact HIV DNA * `uuid`: unique participant identifier * `intact_dna`: Intact HIV DNA count per 1e+6 T-cells (minimum over two measurements)corrected by the DNA shearing index (DSI) * `DnaCopies30ul`: Intact HIV DNA count per 30 uL * `data_plasma_protein.csv` contains plasma protein concentrations for seven cytokines * `uuid`: unique participant identifier * `IP_10`: IP\_10 cytokine concentration (pg/mL), gene = CXCL10 * `G_CSF`: G\_CSF cytokine concentration (pg/mL), gene = CSF3 * `Pentraxin_3`: Pentraxin\_3 concentration value (pg/mL), gene = PTX3 (TNFAIP5) * `IL_1beta`: IL\_1beta cytokine concentration (fg/mL), gene = IL1B * `IL_10`: IL\_10 cytokine concentration (fg/mL), gene = IL-10 * `TNF_alpha`: TNF\_alpha cytokine concentration (fg/mL), gene = TNF-Alpha * `sTLR4`: sTLR4 cytokine concentration (pg/mL), gene = TLR4 * `data_rnaseq_count.csv` contains the RNAseq count data for each of our patients * `uuid`: unique participant identifier * `ENSG00000223972.5`: gene counts corresponding to a specific gene Ensembl * `ENSG00000227232.5`: gene counts corresponding to a specific gene Ensembl * `...` There are 60720 total gene Ensembl counts measured, each is shown in its own column.