Biomedical subjects

Rashmi Sinha

Publications and source records attributed to Rashmi Sinha.

3 recordsLinked to original sources

PubMed2026

Fecal immunochemical tests from population-based colorectal cancer screening programs support prospective microbiome cohorts.

BACKGROUND: Large, prospective cohorts are needed to research the gut microbiome's role in colorectal cancer (CRC) risk. We evaluated the gut microbiome leveraging residual fecal immunochemical tests (FIT) from a CRC screening program in Turin, Italy, and conducted one of the largest population-based case-control studies across the adenoma-carcinoma sequence to date. METHODS: We extracted DNA from residual FIT stool, used whole-genome shotgun sequencing, and included those with CRC (N = 44), advanced adenomas (N = 269), early adenomas (N = 134), and FIT-negative controls (N = 478). Alpha diversity, beta diversity, and species, gene, and pathway relative abundances were estimated. Multivariable logistic regression models were used to estimate associations of these metrics with colorectal neoplasms. RESULTS: Alpha diversity was mostly inversely associated with colorectal neoplasms, particularly early adenomas (OR: 0.45, 95% CI: 0.25-0.80; P = 0.01). Presence of oral pathogens, including Parvimonas micra, was associated with higher odds of CRC. Furthermore, Escherichia coli and Bacteroides fragilis were strongly associated with higher odds of all colorectal neoplasms. Several genes and pathways were associated with colorectal neoplasms. CONCLUSIONS: Our findings align with smaller studies of the gut microbiome and colorectal neoplasms, supporting that CRC screening programs provide opportunities to prospectively study the gut microbiome's association with cancer risk in large populations.

Humans↗

PubMed2025

Insulinemic and inflammatory dietary patterns and colorectal cancer risk: a dietary data harmonization study of one million participants in the Consortium of Metabolomics Studies (COMETS).

BACKGROUND: Inflammatory and insulinemic dietary patterns have been associated with colorectal cancer (CRC) risk, but generalizability across diverse populations with heterogeneous food supplies and dietary behaviors has not been established. OBJECTIVES: We harmonized disparate dietary and covariate data on a large scale to compute the reverse Empirical Dietary Index for Hyperinsulinemia (rEDIH), reverse Empirical Dietary Inflammatory Pattern (rEDIP), and Healthy Eating Index (HEI)-2015 scores, and tested their associations with CRC risk. METHODS: We leveraged data among 501,892 women and 407,390 men from 6 cohorts across the United States (NIH-AARP, Multi-Ethnic Study of Atherosclerosis, Prostate, Lung, Colorectal, and Ovarian, SCCS) and Europe (EPIC, ATBC) with varying sociodemographic characteristics, participating in the Consortium of Metabolomics Studies. We harmonized nomenclature and nutritional information of >800 unique food items across cohorts. We used multivariable-adjusted Cox regression, adjusting for demographic, clinical, and lifestyle factors, to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between the dietary indices and CRC risk per cohort, then meta-analyzed the estimates. RESULTS: During a median follow-up of 14.9 y, 16,525 incident CRC cases were diagnosed. Participants in the highest quintile of rEDIH (low-insulinemic diet) had an 18% reduced risk of CRC (HR: 0.82; 95% CI: 0.78, 0.86) compared with those in the lowest quintile. For the same comparison, similar risk reductions were observed for rEDIP (anti-inflammatory diet) (HR: 0.84; 95% CI: 0.80, 0.89) and HEI-2015 (overall dietary quality) (HR: 0.80; 95% CI: 0.76, 0.85). Heterogeneity between cohorts in the meta-analyzed estimates was low for rEDIH (I2 = 22.3%) compared with rEDIP (I2 = 62.5%) and HEI-2015 (I2=83.9%). CONCLUSIONS: Using carefully harmonized data from nearly 1 million individuals in the United States and Europe, we observed significant CRC risk reduction with habitual intake of low-insulinemic and anti-inflammatory dietary patterns, comparable with higher overall dietary quality. Study findings underscore the utility of these dietary patterns for global cancer prevention efforts.

Humans↗

PubMed2025

Animal farming and the oral microbiome in the Agricultural Health Study.

BACKGROUND: Raising farm animals imparts various exposures that may shape the human microbiome. The oral microbiome has been increasingly implicated in disease development. Animal farming has also been associated with certain chronic diseases such as cancer; however, underlying biological mechanisms are unclear. We investigated associations between raising farm animals and the oral microbiome in the Agricultural Health Study. METHODS: This analysis included 1,245 participants (865 farmers and 380 spouses) who provided oral wash specimens and information on types and numbers of specific animals raised on their farms within 2 years before sample collection. The oral microbiome was measured by sequencing the V4 region of the 16S ribosomal RNA gene. We evaluated associations of farm animal exposures with alpha and beta diversity metrics (within- and between-sample diversity, respectively), as well as presence and relative abundance of specific bacterial genera. All analyses adjusted for potential confounders (e.g., age, sex, smoking, alcohol consumption). RESULTS: Overall, 63 % of participants raised farm animals, most commonly cattle (46 %) and hogs (20 %). Those who raised a large number of hogs (≥2,000 vs. no hogs) had higher alpha diversity. Conversely, raising sheep/goats and raising larger numbers of poultry were associated with lower alpha diversity. Beta diversity was not significantly different between participants with and without any farm animals. Participants raising any farm animals had higher relative abundance of Porphyromonas and lower relative abundances of Prevotella and Ruminococcaceae UCG-014. Several genera were more likely to be absent with specific animal exposures (e.g., Capnocytophaga for cattle and sheep/goats; Corynebacterium, Dialister, Stomatobaculum, and Solobacterium for sheep/goats and poultry). CONCLUSIONS: This was the largest study of farm animal exposures and the human microbiome to date. Findings suggest that raising specific farm animals may influence the oral microbiome, supporting the need to further investigate the potential role of animal farming in disease etiology.

Microbiota↗