Fecal Metagenomes in Colorectal Cancer: Case-Control

Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10-5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.

Classified as human gut / stool / blood / tissue / internal fluids shotgun DNA metagenome of adult and elderly by deterministic_prior with confidence 0.90. Assay shotgun_dna.

• host external_curation.infant_catalog · “infant triage reason_code age_adult_only”
• body site study.title · “Meta-analysis of fecal metagenomes reveals global”
• body site study.description · “and technically diverse fecal shotgun metagenomic studies”
• body site study.description · “production of secondary bile acids from CRC”
• life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”
• life stage sample.attr.host_age · “64 (n=25/82)”

260 runs over 82 samples · mean 1.57 Gbp per run (median 0.76 Gbp, total 407.05 Gbp; 260 runs with a base count) · layout PAIRED 130, SINGLE 130 · platform ILLUMINA 260 · models Illumina HiSeq 4000 (132), Illumina HiSeq 2000 (128) · 88% of runs with a Sandpiper profile · first public 2018-08-14

Wirbel J first · Pyl PT · Kartal E · Zych K · Kashani A · Milanese A · Fleck JS · Voigt AY · Palleja A · Ponnudurai R · Sunagawa S · Coelho LP · Schrotz-King P · Vogtmann E · Habermann N · Niméus E · Thomas AM · Manghi P · Gandini S · Serrano D · Mizutani S · Shiroma H · Shiba S · Shibata T · Yachida S · Yamada T · Waldron L · Naccarati A · Segata N · Sinha R · Ulrich CM · Brenner H · Arumugam M · Bork P · Zeller G last · Zeng S first · Patangia D · Almeida A · Zhou Z · Mu D · Paul Ross R · Stanton C · Wang S last · Li S · Ying J · Wang H · Qu Y · Niu X · Mancabelli L first · Milani C · De Biase R · Bocchio F · Fontana F · Lugli GA · Alessandri G · Tarracchini C · Viappiani A · De Conto F · Nouvenne A · Ticinesi A · Bussolati O · Meschi T · Cecchi R · Turroni F · Ventura M last · van Sinderen D · Wu Y first · Ji G · Han D · Zhang Y · Zhu X · Li H · Li M · Gao Y · Xie R · Xu M · Lu L · Deng Z · Wei Q · Qin H · Bi D last · Xiang H first · Shen B · Lao W · Bai B · Chen M · Zhou L · Yu G · Zhang W · Chen H · Wang Y · Jiang H · Song Z last · Wang Z first · Guo S · Li J · Huang Q · Ning J · Xia B · Lv X · Liu X · Gao Z · Liu L · Song M · Wang J last

PRJEB27928.csv.gz (3.9 KB) · parquet (76.2 KB) — all 82 samples, every field with route and confidence · PRJEB27928_determinations.csv.gz (9.9 KB) — 1,066 evidence rows