ObjectivesOsteoporosis, a prevalent skeletal disorder characterized by reduced bone strength, is closely linked to the IGF system, crucial for skeletal metabolism. However, the precise nature of this relationship remains elusive. In this study, we employed Mendelian randomization (MR) to unravel the associations between genetically predicted serum IGF system member levels and osteoporosis.MethodsA two-sample MR approach was employed to investigate these causal associations based on two individual datasets. Predictions of 14 serum levels of IGF system members were made using 11,036,163 relevant Single Nucleotide Polymorphisms (SNPs) within a cohort of 4,301 individuals of European descent. Genetic association estimates for osteoporosis were derived from two publicly available GWAS consortia: the Finnish consortium from the FinnGen biobank, comprising 212,778 individuals of Finnish descent (3,203 cases and 209,575 controls), and the UK consortium from the UK Biobank, including 337,159 individuals of European descent (5,266 cases and 331,893 controls).ResultsAccording to the UK dataset, IGF-1 levels were associated with a reduced risk of osteoporosis, as indicated by the weighted median method (Odds Ratio [OR] = 0.998, 95% CI = 0.997–1.000, P = 0.032). Additionally, higher levels of IGFBP-3 were linked to a decreased risk of osteoporosis using the Inverse-Variance Weighted (IVW) method (OR = 0.999, 95% CI = 0.998–1.000, P = 0.019), and CTGF levels exhibited a negative association with osteoporosis, as determined by the weighted median method (OR = 0.998, 95% CI = 0.996–0.999, P = 0.004). In the FinnGen dataset, IGF-1 and IGFBP-3 were not identified to be associated with osteoporosis. While, IGF-LR1 levels displayed a negative association with osteoporosis, according to the MR-Egger method (OR = 0.886, 95% CI = 0.795–0.987, P = 0.036), while CYR61 was linked to an increased risk of osteoporosis based on both the weighted median and IVW methods (OR = 1.154, 95% CI = 1.009–1.319, P = 0.037, and OR = 1.115, 95% CI = 1.022–1.215, P = 0.014, respectively).ConclusionThis study provides compelling evidence that certain IGF family members play a role in the pathogenesis of osteoporosis between different datasets, indicating population specific causal effects between IGF family and osteoporosis. Although the results from both datasets demonstrated that IGF family involved in the pathogenesis of osteoporosis, but the responding key molecules might be various among different population. Subsequent research is warranted to evaluate the potential of these biomarkers as targets for osteoporosis prevention and treatment in specific population.

The NIHR Bioresource consists of several groups of participants: ~70k from the general population and blood donors (COMPARE, INTERVAL and STRIDES studies); ~19k with one of ~50 rare diseases (RD) including a ~5k pilot for GEL; ~30k with Inflammatory Bowel Disease (IBD) which include the members of Gut Reaction, the Health Data Research Hub for IBD; and ~20k with Anxiety or depression (GLAD study). It intends to extend recruitment in all areas, and to other rare and common disease groups, with a target of ~300k by 2022. SNP chip data can be used to impute many of the (non-rare) SNPs not included on the chips. The NIHR BioResource is using a modified version of the UK Biobank protocol to improve the options for recall.

The NIHR Bioresource consists of several groups of participants: ~70k from the general population and blood donors (COMPARE, INTERVAL and STRIDES studies); ~19k with one of ~50 rare diseases (RD) including a ~5k pilot for GEL; ~30k with Inflammatory Bowel Disease (IBD) which include the members of Gut Reaction, the Health Data Research Hub for IBD; and ~20k with Anxiety or depression (GLAD study). It intends to extend recruitment in all areas, and to other rare and common disease groups, with a target of ~300k by 2022. The NIHR BioResource extracts DNA from blood and saliva samples taken at recruitment, and measures a panel of SNPs on each DNA sample, using a commodity SNP genotyping array from e.g. Illumina or Affymetrix (now Thermofisher). This is used to pre-screen or match participants when inviting them to take part in experimental medicine studies. De-identified versions of this data is available to researchers investigating the feasibility of future studies. The Technical Metadata describes a SNP annotation file – i.e. what the chip is measuring. The file itself has as many rows as there are SNPs represented on the chip, and is proprietary to the manufacturer, although deeply familiar to researchers.