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Expanding the ASXL1 Mutation Spectrum: Transcriptomic and Metabolic Dysregulation Underlying Overgrowth Phenotype in Inherited ASXL1 Missense Mutations

GSE337807 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2026/07/11 Platform GPL24676Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 11 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
11 samples: 3 × proband fibro vs 3 × father fibroGroups 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.
Summary (written by the submitters)
Mutations in genes associated with chromatin remodeling, such as Additional sex combs-like 1 (ASXL1), underlie a spectrum of congenital abnormalities and neurodevelopmental disorders. Pathogenic variants in ASXL1 are classically associated with Bohring–Opitz syndrome (BOS), a severe developmental disorder caused predominantly by de novo truncating mutations.
Read the full summary ↓
In this study, we present a 14-year-old female with overgrowth, macrocephaly, and normal neurodevelopment, features that diverge from the typical BOS phenotype. This proband was found to carry a paternally-inherited ASXL1 missense mutation (c.4562C>T p.Ala1521Val) in the plant homeodomain (PHD), a variant of unknown significance (VUS). To investigate its functional impact, we performed integrated transcriptomic (RNA-seq) and metabolomic profiling of peripheral blood and patient-derived fibroblasts, with comparison to unaffected controls and previously characterized BOS samples. Transcriptomic analysis demonstrated that ASXL1 missense carriers exhibit a gene expression profile distinct from BOS. Cross-tissue integration identified 104 shared differentially expressed genes, significantly enriched for oxidative phosphorylation pathways. Notably, mitochondrial genes were downregulated in blood but upregulated in fibroblasts, suggesting tissue-specific metabolic adaptation. Metabolomic profiling revealed depletion of glycolytic intermediates and reduced levels of key energy carriers, including NAD⁺ and NADPH, indicating impaired energy metabolism. In contrast to BOS, which is characterized by transcriptional de-repression and increased glycolytic activity, ASXL1 missense cells demonstrated a predominantly repressive transcriptional profile and diminished bioenergetic capacity. These findings define a distinct molecular and metabolic signature associated with ASXL1 missense variation and support an expanded phenotypic spectrum beyond classical BOS.
This dataset
Open GSE337807 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 GSE337807_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 PRJNA1491115 and SRA study SRP715898. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × proband fibro vs 3 × father fibro

Supports a between-group comparison across 6 samples.

How we read this: 2 replicated groups read from 11 sample titles; they account for 6 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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