`R/data.R`

`df_linear_associations.Rd`

A data frame containing cross-sectional associations of the Nightingale blood biomarkers to Body Mass Index (BMI), insulin resistance (log(HOMA-IR)) and fasting glucose. For these values a linear regression model was used, adjusted for age and sex.

`df_linear_associations`

A data frame (tibble) with 687 rows and 5 columns:

- name
Blood biomarker name. Note: glucose is missing as the results are adjusted for this biomarker.

- trait
The response variable of the regression model, either BMI, log(HOMA-IR) or fasting glucose.

- beta
Linear regression coefficient \(\beta\).

- se
Standard error.

- pvalue
P-value.

These data are taken from the Supplementary material of A. V. Ahola-Olli et al. (2019). https://www.biorxiv.org/content/early/2019/01/08/513648

"Values are beta-correlations from cross-sectional metabolite associations with BMI, log(HOMA-IR) and fasting glucose. For comparison of the patterns of associations, magnitudes are scaled to 1-SD in each of the outcomes (corresponding to 4.2 kg/m2 for BMI, 0.57 for log(HOMA-IR) and 0.56 mmol/l for glucose) per 1-SD log-transformed metabolite concentration. Results were adjusted for sex and age, and meta-analyzed for 11,896 individuals from the four cohorts. Error bars denote 95% confidence intervals; the large sample size and consistency across cohorts make confidence intervals narrow for the cross-sectional linear regression analyses." The values are shown in Figure S5 of A. V. Ahola-Olli et al. (2019): https://www.biorxiv.org/content/early/2019/01/08/513648