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L. Lahti

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Open access Sep 2026

Population scale analysis reveals gut microbiome diversity and functional shifts linked to obesity

Summary This study investigated the relationship between the gut microbiota and two obesity indicators, body mass index (BMI) and waist-hip ratio (WHR) in a well-phenotyped random population sample of 5846 participants. Associations were tested using multivariable-adjusted linear models and validated for BMI in an exte...

L. Yeo, J. Palmu, A. Havulinna et al. · 1 citation
Open access Sep 2026

A gut microbiome-derived risk score is associated with future cancer development

Cancer remains a leading cause of morbidity and mortality worldwide, and the incidence of new cancer cases is rising. While established lifestyle factors such as smoking, obesity, and diet contribute to cancer risk, the gut microbiome has emerged as a hallmark of cancer. However, the role of the gut microbiome in cance...

E. Oosterhout, R. S. Leijdesdorff, O. Kambur et al. · 0 citations
Sep 2026

Gut microbiome alterations predictive of cancer risk

It is shown that people who are diagnosed with cancer after microbiome sampling have microbiome alterations like those found in diagnosed cancer cases, albeit to a lower degree, across the four populations studied, indicating that the microbiome may evolve towards the one found in cancer well before cancer is diagnosed...

G. Vitali, J. Bjork, O. Kambur et al. · 0 citations
Open access Aug 2026

A spectrum of gut microbiota signatures predicts long-term health status

It is demonstrated that robust signatures of co-abundant species can be prospectively associated with mortality, diabetes, liver disease, and sepsis risk among Finnish adults in the FINRISK population cohort based on a 20-year follow-up.

Himmi Lindgren, Chandler Ross, M. Ruuskanen et al. · 0 citations
Open access Aug 2026

Joint-RPCA: domain-aware multi-omics integration for systems microbiology.

Joint Robust Principal Component Analysis (Joint-RPCA), a method designed with these statistical properties in mind and broadly applicable to multi-omics settings with similar challenges, reveals replicable and interpretable multi-omic patterns.

Bianca Cordazzo Vargas, C. Martino, A. Dilmore et al. · 1 citation

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