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Autophagy-enhancing ATG16L1 polymorphism improves clinical outcomes and promotes superior T-cell immunity in chronic HIV-1 infection

GSE253769 Homo sapiens (human) RNA-seq (gene expression) 32 samples Submitted 2024/03/04 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 32 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
32 samples: 8 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Autophagy-enhancing ATG16L1 polymorphism is associated with improved clinical outcome and T-cell immunity in chronic HIV-1 infectionNature communications · 2024
Summary (written by the submitters)
Chronic HIV-1 infection is characterized by T-cell dysregulation that is partly restored by antiretroviral therapy. Autophagy is a critical regulator of T-cell function. Here, we demonstrate a protective role for autophagy in HIV-1 disease pathogenesis. Targeted analysis of genetic variation in core autophagy gene ATG16L1 revealed the previously unidentified rs6861 polymorphism, which correlated functionally with enhanced autophagy and clinically with improved survival of untreated HIV-1-infected individuals.
Read the full summary ↓
T cells carrying ATG16L1 rs6861(TT) genotype displayed superior antiviral immunity, evidenced by increased proliferation, revamped immune responsiveness and suppressed exhaustion/immunosenescence features. In-depth flow-cytometric and transriptional profiling revealed T-helper-cell-signatures unique to rs6861(TT) individuals with enriched regulation of pro-inflammatory networks and skewing towards immunoregulatory phenotype. Therapeutic enhancement of autophagy recapitulated the rs6861(TT)-associated traits in non-carriers. These data underscore the in vivo relevance of autophagy for longer-lasting T-cell-mediated HIV-1 control, with implications towards development of host-directed antivirals targeting autophagy to restore immune function in chronic HIV-1 infection.
Published in
Autophagy-enhancing ATG16L1 polymorphism is associated with improved clinical outcome and T-cell immunity in chronic HIV-1 infection
Schreurs RRCE, Koulis A, Booiman T et al. · Nature communications 2024 · PMID 38548722 · doi:10.1038/s41467-024-46606-z
This dataset
Open GSE253769 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE253769_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1067099 and SRA study SRP484917. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38548722) ↗
Study design
8 conditions, mostly in duplicate
CD4T cells, rs6861(CC) genotyped donor 1, ant… ×2 CD4T cells, rs6861(TT) genotyped donor 1, ant… ×2 CD4T cells, rs6861(TT) genotyped donor 2, ant… ×2 CD4T cells, rs6861(CC) genotyped donor 2, ant… ×2 CD4T cells, rs6861(CC) genotyped donor 3, ant… ×2 CD4T cells, rs6861(CC) genotyped donor 4, ant… ×2 CD4T cells, rs6861(TT) genotyped donor 3, ant… ×2 CD4T cells, rs6861(TT) genotyped donor 4, ant… ×2 +16 more

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 32 sample titles; they account for 16 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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