Multi-Omics Analysis

Bulk RNAseq (618 donors across 3 cohorts) — Explore all donors → • Proteomics (3,173 participant tracking records) • Metabolomics (MTBLS5568: 12 donors with full profiles + 1,197 tracking records)

618Bulk RNAseq Donors

193 gse221521 (med 12,583,766 counts)

279 gse255685 (med 2 counts)

146 gse182409 (med 70,892,994 counts)

9,849Marker Gene Entries

Bulk RNAseq Donors per Dataset

Total Expression Count Distribution

Mitochondrial Fraction Distribution

Detected Genes per Donor

Immune Marker Gene Categories

Top 20 Marker Genes

ds-gse182409: Expression by Health Status

ds-gse221521: Expression by Health Status

ds-gse255685: Expression by Health Status

Immune Marker Gene Expression (Top 30 by Median FPKM)

S100A9

Median 15.6 FPKM

Samples 618

FCGR3B

Median 14.7 FPKM

Samples 618

LYZ

Median 14.5 FPKM

Samples 618

S100A8

Median 14.3 FPKM

Samples 618

GNLY

Median 12.2 FPKM

Samples 618

CD3E

Median 12.0 FPKM

Samples 618

NKG7

Median 11.8 FPKM

Samples 618

CXCL8

Median 11.6 FPKM

Samples 618

CD3D

Median 10.4 FPKM

Samples 618

MS4A1

Median 7.0 FPKM

Samples 618

IL1B

Median 8.3 FPKM

Samples 617

MPO

Median 5.5 FPKM

Samples 616

MT-CO1

Median 16.6 FPKM

Samples 472

MT-CO2

Median 15.6 FPKM

Samples 472

MT-ND1

Median 15.5 FPKM

Samples 472

HBA2

Median 324.7 FPKM

Samples 339

HBB

Median 177.1 FPKM

Samples 339

HBA1

Median 808.9 FPKM

Samples 309

Open Proteomics Analysis → GNHS pQTL panel × CIMA coverage, shared core proteome & RA differential

3,116Proteomics Participants (total)

3Proteomics Datasets

Dataset	Participants	Matrix	Assay	Repository	Status	Access
Han Chinese serum proteome pQTL / GNHS + WEBIRTH	2,958	Serum	DIA-MS	iProX / ProteomeXchange	Public repository and pQTL browser registered	Open
CRC plasma proteomics, Zhejiang discovery cohort	150	Plasma	TMT-MS	iProX / ProteomeXchange	Public repository and source data registered	Open
RA serum proteomics, Guangzhou	8	Serum	LC-MS/MS	PRIDE / ProteomeXchange	Public repository registered	Open

Proteomics data are raw mass spectrometry files (WIFF/WIFF.SCAN) on pandora002. Per-donor protein abundance matrices are not yet extracted. The 2,958 Han Chinese pQTL dataset has public browser access at Westlake Omics; CRC (200) and RA (15) datasets have public repository raw data.

1,209Metabolomics Participants (total)

8Metabolomics Datasets

1 / 8With Local Data (MTBLS5568)

Dataset	Participants	Matrix	Scope	Repository	Status
MTBLS13155	315	Plasma	Plasma manganese, gut microbiota, and glucose metabolism study	MetaboLights	Not yet downloaded
MTBLS352	293	Fasting plasma	Normal glucose tolerance, prediabetes, and type 2 diabetes lipidomics cohort	MetaboLights	Not yet downloaded
MTBLS11996	242	Plasma	Hepatocellular carcinoma, benign hepatic lesion, and healthy donor metabolomics	MetaboLights	Not yet downloaded
MTBLS12968	149	Mid-trimester plasma	Pregnancy cohort stratified by PCOS and preterm delivery status	MetaboLights	Not yet downloaded
MTBLS12820	136	Serum	Dampness-heat gout and healthy control cohort	MetaboLights	Not yet downloaded
MTBLS13501	25	Serum	ASD children before and after Dachaihu decoction treatment	MetaboLights	Not yet downloaded
MTBLS9664	37	Plasma	COVID-19 viral sepsis and non-sepsis profiles	MetaboLights	Not yet downloaded
MTBLS5568	12	Plasma	Prediabetes whey-protein intervention in Asian Chinese and European Caucasian women	MetaboLights	14 GB local (pandora002)

MTBLS5568 — Available Metabolite Data

12 Asian Chinese participants (of 24 total)

2 LC-MS modes: positive + negative HILIC

591 mzML spectral files (14 GB)

2 Metabolite abundance matrices (maf.tsv)

MTBLS5568 is a prediabetes postprandial whey-protein intervention study. Only the 12 Asian Chinese participants are included in the China immune atlas. Positive and negative mode metabolite abundance matrices are available on pandora002. The remaining 7 MTBLS datasets (1,197 participants) are listed on MetaboLights but not yet downloaded to local storage.

4,943Total Multi-Omics Donors/Participants

618Bulk RNAseq (3 datasets, local)

3,116Proteomics (3 datasets, public repo)

1,209Metabolomics (8 datasets, 1 local)

9,849Immune Marker Gene Entries (Bulk)

Multi-Omics Dataset Coverage

Participants by Multi-Omics Dataset

Data Availability Matrix

Modality	Datasets	Participants	Local Data	Per-Donor Data	Analysis Ready
Bulk RNAseq	3	618	Full (383 MB)	Yes — 618 expression profiles	Yes — QC + marker genes
Proteomics	3	3,173	Partial (21 GB raw MS)	No — raw spectra only	Not yet
Metabolomics	8	1,209	1/8 (MTBLS5568, 14 GB)	12 donors (MTBLS5568 only)	MTBLS5568 only

Analysis generated 2026-08-01. Bulk RNAseq QC metrics and marker gene expression are derived from public GEO processed data. Proteomics raw data requires DIA-NN/Spectronaut processing. Metabolomics raw mzML requires XCMS/MZmine processing.

428CIMA Donors (integrated)

1,756Significant Associations (FDR<0.05)

1,205Immune × Metabolomics

367Immune × Blood Biochemistry

184Immune × Phenotype (age/BMI…)

|ρ|=0.63Strongest Edge (gdT1_TRDV1 × age)

Immune Cell / Feature	Target	ρ	FDR
RNA:gdT1_TRDV1	age	-0.63	4.1e-45
ATAC:CD8_Tn_CCR7	age	-0.57	1.1e-32
RNA:CD4_Tn_SOX4	age	-0.56	2.0e-33
RNA:CD8_Tn_SOX4	age	-0.52	7.7e-29
RNA:CD8_Tn_CCR7	age	-0.50	1.7e-25
ATAC:MAIT_SLC4A10	age	-0.46	3.1e-20
ATAC:gdT2_IL12RB2	age	-0.46	1.1e-19
RNA:CD8_Tem_CCR7neg	age	0.41	1.0e-16
RNA:gdT2_IL12RB2	age	-0.37	2.9e-13
ATAC:CD8_CTL_GZMB	age	0.36	6.6e-12

Immune-aging axis (top features vs age, Spearman). Naive/innate immune cells decline with age (negative ρ); effector/regulatory subsets increase — a canonical immunosenescence pattern. Full report: CIMA Multi-Omics Network Report.

Cross-Omics Correlation Network (top 250)

Immune × Blood Biochemistry (heatmap)

RNA × Metabolomics (heatmap)

Top Scatter

MOFA Factor Scatter

MOFA Key Factors

MOFA Variance Explained

MOFA+ Factor Variance Explained

Factor	RNA	ATAC	Biochem	Metabolomics	Total
Factor1	0.337%	0.012%	2.238%	20.707%	23.29%
Factor2	1.394%	1.892%	12.800%	1.919%	18.01%
Factor3	0.079%	0.236%	0.341%	7.463%	8.12%
Factor4	0.291%	0.134%	1.228%	5.190%	6.84%
Factor5	0.396%	0.464%	0.991%	3.116%	4.97%
Factor6	0.036%	0.036%	1.326%	3.019%	4.42%
Factor7	0.344%	0.436%	0.870%	1.918%	3.57%
Factor8	0.533%	0.527%	0.888%	1.064%	3.01%
Factor9	0.026%	0.039%	0.057%	2.859%	2.98%
Factor10	0.316%	0.139%	0.359%	2.012%	2.83%
Factor11	0.112%	0.287%	0.709%	1.601%	2.71%
Factor12	0.535%	0.477%	0.335%	0.952%	2.30%
Factor13	0.042%	0.082%	0.895%	1.258%	2.28%
Factor14	0.114%	0.117%	1.178%	0.658%	2.07%
Factor15	0.037%	0.048%	0.506%	1.218%	1.81%
Factor16	0.053%	0.060%	0.030%	1.611%	1.75%
Factor17	0.433%	0.512%	0.149%	0.527%	1.62%
Factor18	0.233%	0.101%	0.814%	0.440%	1.59%
Factor19	0.056%	0.029%	0.028%	1.238%	1.35%
Factor20	0.031%	0.023%	0.353%	0.783%	1.19%
Factor21	0.149%	0.161%	0.240%	0.450%	1.00%
Factor22	0.033%	0.259%	0.018%	0.604%	0.91%
Factor23	0.007%	0.012%	0.015%	0.829%	0.86%
Factor24	0.097%	0.014%	0.019%	0.540%	0.67%
Factor25	0.060%	0.028%	0.053%	0.368%	0.51%

MOFA Factor × Phenotype Associations (FDR<0.05)

Factor	Phenotype	ρ	FDR
Factor2	weight	0.640	8.94e-40
Factor2	BMI	0.520	9.83e-24
Factor2	height	0.466	1.90e-18
Factor5	age	0.356	2.08e-10
Factor17	age	0.333	2.54e-9
Factor8	age	-0.300	9.92e-8
Factor2	age	0.285	4.45e-7
Factor14	age	0.248	1.56e-5
Factor12	age	-0.239	2.79e-5
Factor1	BMI	0.246	5.11e-5
Factor11	age	-0.202	5.53e-4
Factor1	weight	0.206	1.46e-3
Factor18	age	-0.182	2.05e-3
Factor8	height	0.179	1.10e-2
Factor11	BMI	-0.162	2.22e-2
Factor12	BMI	-0.146	3.26e-2
Factor5	BMI	0.144	3.26e-2
Factor17	BMI	0.145	3.26e-2
Factor24	age	0.135	3.40e-2
Factor15	age	0.132	3.41e-2
Factor10	age	0.127	4.17e-2
Factor5	weight	0.150	4.25e-2

MOFA+ multi-omics factor integration (RNA / ATAC / blood biochemistry / plasma metabolomics, 428 donors). Source analysis: pandora002 /mnt/disk1/ChineseImmuneAtlas20260707/analysis/output, generated 2026-08-09.