Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health
Sparks et al., Nature Medicine, 2024
Abstract
Monogenic diseases are often studied in isolation. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with healthy controls. We identified both disease-specific and “pan-disease” signatures and found that inter-individual variations tend to dominate over those attributable to disease conditions or medication use. Both unsupervised analysis of individual immune states and machine learning classification distinguishing age- and sex-matched healthy subjects from monogenic patients converged to a metric of immune health (IHM). In independent datasets, the IHM discriminates healthy from polygenic autoimmune and inflammatory disease states, marks healthy aging, tracks disease activities and treatment responses, and predicts age-dependent antibody responses to vaccination. Thus, deviations from health in diverse conditions and manifestations, including aging, have shared immune consequences, whereby the IHM can quantify immune health even among clinically healthy individuals beyond classic inflammatory markers such as CRP and IL-6. Our work provides tools and a framework for studying human immune health.
Subject Demographics
Number of samples
Due to privacy consideration and patient consent restrictions, only aggregated mean expression profiles and clinical measurements by condition
are shown here. Conditions with only one primary subject/sample are excluded.
Subject-level data can be requested through dbGaP using the study accession number
phs002732
.
Microarray Gene Expressions
Download tableSomalogic Serum Protein Levels
Download tableCBC & TBNK Measurements
Download tableTranscripional Module (TM) Membership
Download tableProtein Module (PM) Membership
Download table
Differentially expressed (FDR < 0.05) markers for each condition compared to healthy controls are listed below. Click
here
to download all of the markers as a .csv file.
CBC & TBNK Markers
Transcripional Module (TM) Markers
Protein Module (PM) Markers
Module Gene Markers
Module Protein Markers
IHM Components
Download tableTranscriptomic Surrogate Signature
Download tableProtein Surrogate Signature
Download tableEstimate the IHM surrogate signature scores for your own samples by uploading their expression profiles in .csv or .tsv format (maximum size: 10 MB),
with genes or proteins listed in the rows and samples in the columns. Please bear in mind that the IHM signatures were developed using gene expression
data from whole blood and serum proteins. Exercise caution when interpreting the results, particularly if your data originate from other tissue types.
Sample datasets:
gene matrix with EntrezGene symbols
,
protein measurements with UniProt ID
Step 1: Specify row ID type
Step 2: Upload data