Biology subjects

Riboli, E.

Publications and source records attributed to Riboli, E..

3 recordsLinked to original sources

bioRxiv2025

High-throughput plasma proteomic platforms: Insights from a multi-ethnic Asian cohort

We compared three leading affinity-based and mass-spectrometry-based proteomic platforms (SomaScan11K, Olink Explore HT, Orbitrap Astral with Seer Proteograph [MS-Seer]) in a multi-ethnic Asian cohort, to inform biomarker discovery and functional genomic studies of global populations. We found limited overlap (1,740 proteins) across the three platforms, with modest correlations (0.34-0.10). SomaScan had lower missingness (<1%) and CV (<10%), compared to Olink (51%, 23%) and MS-Seer (12%, 19%). The new assays in Olink Explore HT (absent in Explore3072) primarily drove its higher missingness and CV. The number of phenotypic associations varied by trait, while the number of genetic associations (cis-pQTLs at P<5e-08) were similar for Olink and SomaScan. Protein levels differed between ethnicities, with SomaScan identifying more ethnicity-differentiated proteins than Olink (FDR<0.05). Finally, SomaScan ANML normalization attenuated biologically relevant associations in our study. These findings underscore the importance of platform evaluation and data normalization strategies for application in large-scale, diverse population cohorts.

bioinformatics↗

bioRxiv2020

Coffee consumption and risk of breast cancer: a Mendelian Randomization study

BackgroundObservational studies have reported either null or weak protective associations for coffee consumption and risk of breast cancer. MethodsWe conducted a two-sample Mendelian randomization randomization (MR) analysis to evaluate the relationship between coffee consumption and breast cancer risk using 33 single-nucleotide polymorphisms (SNPs) associated with coffee consumption from a genome-wide association (GWA) study on 212,119 female UK Biobank participants of White British ancestry. Risk estimates for breast cancer were retrieved from publicly available GWA summary statistics from the Breast Cancer Association Consortium (BCAC) on 122,977 cases (of which 69,501 were estrogen receptor (ER)-positive, 21,468 ER-negative) and 105,974 controls of European ancestry. Random-effects inverse variance weighted (IVW) MR analyses were performed along with several sensitivity analyses to assess the impact of potential MR assumption violations. ResultsOne cup per day increase in genetically predicted coffee consumption in women was not associated with risk of total (IVW random-effects; odds ratio (OR): 0.91, 95% confidence intervals (CI): 0.80-1.02, P: 0.12, P for instrument heterogeneity: 7.17e-13), ER-positive (OR=0.90, 95% CI: 0.79-1.02, P: 0.09) and ER-negative breast cancer (OR: 0.88, 95% CI: 0.75-1.03, P: 0.12). Null associations were also found in the sensitivity analyses using MR-Egger (total breast cancer; OR: 1.00, 95% CI: 0.80-1.25), weighted median (OR: 0.97, 95% CI: 0.89-1.05) and weighted mode (OR: 1.00, CI: 0.93-1.07). ConclusionsThe results of this large MR study do not support an association of genetically predicted coffee consumption on breast cancer risk, but we cannot rule out existence of a weak inverse association.

cancer biology↗

bioRxiv2019

Circulating concentrations of micro-nutrients and risk of breast cancer: A Mendelian randomization study

BackgroundThe epidemiological literature reports inconsistent associations between consumption or circulating concentrations of micro-nutrients and breast cancer risk. We investigated associations between genetically determined concentrations of 11 micro-nutrients (beta-carotene, calcium, copper, folate, iron, magnesium, phosphorus, selenium, vitamin B6, vitamin B12 and zinc) and breast cancer risk using Mendelian randomization (MR).\n\nMaterials and methodsA two-sample MR study was conducted using 122,977 women with breast cancer, of whom 69,501 were estrogen receptor positive (ER+ve) and 21,468 were ER-ve, and 105,974 controls from the Breast Cancer Association Consortium. MR analyses were conducted using the inverse variance weighted approach, and sensitivity analyses were conducted to assess the impact of potential violations of MR assumptions.\n\nResultsOne standard deviation (SD: 0.08 mmol/L) higher genetically determined concentration of magnesium was associated with a 17% (odds ratio [OR]: 1.17, 95% confidence interval [CI]: 1.10 to 1.25, P=9.1 x 10-7) and 20% (OR: 1.20, 95% CI: 1.11 to 1.30, P=3.17 x 10-6) higher risk of overall and ER+ve breast cancer, respectively. An inverse association was observed for a SD (0.5 mg/dL) higher genetically determined phosphorus concentration and ER-ve breast cancer (OR: 0.84, 95% CI: 0.72 to 0.98, P=0.03). A suggestive inverse association was observed for a SD (0.48 mg/dL) higher genetically determined calcium concentration with overall breast cancer (OR: 0.91, 95% CI: 0.83 to 1.00, P=0.06). There was little evidence that any of the other nutrients were associated with breast cancer. The results for magnesium were robust under all sensitivity analyses.\n\nConclusionsHigher circulating concentrations of magnesium, phosphorus and calcium may affect breast cancer risk. Further work is required to replicate these findings and investigate underlying mechanisms.\n\nkey messageWe conducted a Mendelian randomization study to investigate whether concentrations of 11 micro-nutrients are associated with risk of breast cancer. An increased risk of overall and oestrogen-receptor positive disease was observed for genetically higher concentrations of magnesium and inverse associations were observed for phosphorus and calcium concentrations\n\nWhere authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization.

epidemiology↗