No Significant Direct Causal Association Between TNF Pathway Biomarkers and Hip Fracture Risk: A Study Based on Real-World Data

Summary

This study integrates FAERS pharmacovigilance with Mendelian randomization to assess associations between TNF pathway biomarkers and hip fracture risk. Combining real-world adverse-event surveillance with genetic causal inference, the workflow offers a reproducible approach for evaluating biomarker–outcome relationships when randomized trials are unavailable, impractical, or ethically difficult to conduct in practice.

Abstract

Hip fracture is a common and serious condition in elderly individuals, often associated with altered TNF-α signaling. However, few studies have explored whether changes in TNF pathway biomarkers contribute to the risk of hip fracture. In this study, adverse events related to hip fracture reported for five TNF inhibitors were analyzed using data from the first quarter of 2014 to the fourth quarter of 2023. After data standardization and cleaning, four disproportionality methods, including the reporting odds ratio, proportional reporting ratio, multi-item gamma Poisson shrinker, and Bayesian confidence propagation neural network, were applied to assess the association between TNF inhibitor exposure and hip fracture outcomes. Complementary mendelian randomization analyses were further conducted using TNF-α, sTNFR1, and sTNFR2 as exposures and hip fracture as the outcome. Pharmacovigilance analyses revealed no significant association between TNF inhibitor exposure and hip fracture-related adverse events across the four algorithms. Mendelian randomization analyses identified no significant direct causal association between genetically predicted TNF-α and hip fracture risk, and additional analyses of sTNFR1 and sTNFR2 yielded consistent results. These findings suggest that TNF pathway biomarkers are unlikely to act as independent direct determinants of hip fracture risk and may provide a useful basis for future mechanistic studies and prevention strategies.

Introduction

Hip fracture is a common and serious clinical condition in elderly individuals, and its clinical manifestations are usually characterized by hip pain and dysfunction¹. Hip fracture not only has a serious impact on patients but also imposes a heavy burden on families and society. For patients, hip fracture is often accompanied by a long period of hospitalization and rehabilitation, which has a great impact on the physical and mental health of elderly patients^2,3,4. At the family level, patients usually require long-term care from family members, which c....

Protocol

FAERS data sources

The real-world data for this study were obtained from the FAERS database (https://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html). This is a publicly accessible and anonymized database, so ethical approval was not required for this study. Information about the five drugs included is shown in Table 1. The search was performed by first limiting the adverse events to hip fracture, and the search time span was from Q1 2014 to Q4 2023. To ensure reliable and stable data, the study standardized the terminology of reported adverse events via the MedDRA Dictionary version 26.1

Results

Results of descriptive analysis

The detailed data-cleaning and screening workflow is summarized in Figure 2. A total of 15,428,448 records were initially retrieved from the DEMO table. After duplicate removal, 13,447,292 unique DEMO records remained. After data standardization, deduplication, and cross-table linkage, the final numbers of records available in each FAERS table were 27,260,995 in DRUG, 18,851,426 in REAC, 12,573,760 in THER, 6,448,18.......

Discussion

In this study, five TNF inhibitors identified from real-world pharmacovigilance data were integrated with Mendelian randomization analyses to evaluate whether TNF pathway biomarkers are causally associated with hip fracture risk. The findings consistently indicated that no significant direct causal association between TNF-α and hip fracture risk was identified, and additional analyses of sTNFR1 and sTNFR2 yielded concordant results. These results support the value of combining spontaneous-report safety data with gen.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Generic laboratory computer workstation	Equipment	Generic laboratory computer	N/A
FDA Adverse Event Reporting System database	Public pharmacovigilance database	U.S. Food and Drug Administration	https://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html
FAERS quarterly ASCII files	Public pharmacovigilance data files	U.S. Food and Drug Administration	Q1 2014 to Q4 2023; DEMO, DRUG, REAC, THER, RPSR, and OUTC tables
MedDRA Dictionary version 26.1	Medical terminology resource	MedDRA Maintenance and Support Services Organization	https://www.meddra.org/
IEU OpenGWAS database	Public GWAS database	MRC Integrative Epidemiology Unit, University of Bristol	https://gwas.mrcieu.ac.uk/
TNF-α GWAS summary statistics	Exposure GWAS dataset	IEU OpenGWAS database	GWAS ID: prot-c-3722_49_2
sTNFR1 GWAS summary statistics	Exposure GWAS dataset	IEU OpenGWAS database	GWAS ID: prot-c-2654_19_1
sTNFR2 GWAS summary statistics	Exposure GWAS dataset	IEU OpenGWAS database	GWAS ID: prot-c-3152_57_1
GWAS Catalog	Public GWAS database	European Bioinformatics Institute	https://www.ebi.ac.uk/gwas/
Hip fracture GWAS summary statistics	Outcome GWAS dataset	GWAS Catalog	Accession ID: GCST90161240; https://www.ebi.ac.uk/gwas/studies/GCST90161240
R version 4.3.2	Statistical computing environment	R Foundation for Statistical Computing	https://www.r-project.org/
data.table package	R package	R package repository / R community	https://cran.r-project.org/package=data.table
dplyr package	R package	R package repository / R community	https://cran.r-project.org/package=dplyr
readr package	R package	R package repository / R community	https://cran.r-project.org/package=readr
stringr package	R package	R package repository / R community	https://cran.r-project.org/package=stringr
vroom package	R package	R package repository / R community	https://cran.r-project.org/package=vroom
TwoSampleMR version 0.5.6	R package for Mendelian randomization	MRC Integrative Epidemiology Unit	https://mrcieu.github.io/TwoSampleMR/
Custom R scripts for FAERS processing	Analysis script	Prepared by the study authors	Provided as supplementary files
Custom R scripts for Mendelian randomization	Analysis script	Prepared by the study authors	Provided as supplementary files