Causal relationship between immune cells and telomere length: mendelian randomization analysis.

BACKGROUND: The causal relationship between immune cells and telomere length remains controversial. METHODS: Data on the immune cells were obtained from a previous study with 3,757 participants. Data on telomere length were obtained from the OpenGWAS database. Genome-Wide Association Study (GWAS) data were obtained and screened for eligible instrumental variables (IVs) using the TwoSampleMR package and the Phenoscanner database. To investigate the genetic causality between immune cells and telomere length, Mendelian randomization (MR) analysis and Bayesian weighted Mendelian randomization (BWMR) analysis were used. RESULTS: MR analysis showed that there is indeed a genetic causal relationship between immune cells and telomere length. A total of 16 immune cells were successfully validated. A positive correlation was found between telomere length and immune cells such as CD28 + CD45RA + CD8br %CD8br (OR = 1.002, 95%CI: 1.000-1.003). A negative correlation was found between telomere length and immune cells such as Transitional AC (OR = 0.991, 95%CI: 0.984-0.997) (P < 0.05). Reverse MR analysis similarly confirmed that telomere length can affect four types of immune cells, including CD25 on IgD + CD24- (OR = 1.291, 95%CI: 1.060-1.571), at the genetic level. CONCLUSION: There is indeed a mutual genetic causality between immune cells and telomere length, which will provide theoretical basis and support for more subsequent clinical studies.

Genetic causal association between frozen shoulder and carpal tunnel syndrome: a two-sample mendelian randomization.

OBJECTIVE: Observational studies have suggested an association between frozen shoulder (FS) and carpal tunnel syndrome (CTS). However, due to challenges in establishing a temporal sequence, the causal relationship between these two conditions remains elusive. This study, based on aggregated data from large-scale population-wide genome-wide association studies (GWAS), investigates the genetic causality between FS and CTS. METHODS: Initially, a series of quality control measures were employed to select single nucleotide polymorphisms (SNPs) closely associated with the exposure factors. Two-sample Mendelian randomization (MR) was utilized to examine the genetic causality between FS and CTS, employing methods including Inverse-Variance Weighted (IVW), MR-Egger, Weighted Median, Simple Mode, and Weighted Mode approaches. Subsequently, sensitivity analyses were conducted to assess the robustness of the MR analysis results. RESULTS: IVW analysis results indicate a positive causal relationship between CTS and FS (p < 0.05, OR > 1), while a negative causal relationship between the two conditions was not observed. Heterogeneity tests suggest minimal heterogeneity in our IVW analysis results (p > 0.05). Multivariable MR testing also indicates no pleiotropy in our IVW analysis (p > 0.05), and stepwise exclusion tests demonstrate the reliability and stability of the MR analysis results. Gene Ontology (GO) pathway analysis reveals enrichment of genes regulated by the associated SNPs in the TGFß-related pathways. CONCLUSION: This study provides evidence of the genetic causal association between frozen shoulder and carpal tunnel syndrome and provides new insights into the genetics of fibrotic disorders.

Investigating the association between serum ADAM/ADAMTS levels and bone mineral density by mendelian randomization study.

PURPOSE: A Disintegrin and Metalloproteinase (ADAM) and A Disintegrin and Metalloproteinase with Thrombospondin Motif (ADAMTS) have been reported potentially involved in bone metabolism and related to bone mineral density. This Mendelian Randomization (MR) analysis was performed to determine whether there are causal associations of serum ADAM/ADAMTS with BMD in rid of confounders. METHODS: The genome-wide summary statistics of four site-specific BMD measurements were obtained from studies in individuals of European ancestry, including forearm (n = 8,143), femoral neck (n = 32,735), lumbar spine (n = 28,498) and heel (n = 426,824). The genetic instrumental variables for circulating levels of ADAM12, ADAM19, ADAM23, ADAMTS5 and ADAMTS6 were retrieved from the latest genome-wide association study of European ancestry (n = 5336 ~ 5367). The estimated causal effect was given by the Wald ratio for each variant, the inverse-variance weighted model was used as the primary approach to combine estimates from multiple instruments, and sensitivity analyses were conducted to assess the robustness of MR results. The Bonferroni-corrected significance was set at P < 0.0025 to account for multiple testing, and a lenient threshold P < 0.05 was considered to suggest a causal relationship. RESULTS: The causal effects of genetically predicted serum ADAM/ADAMTS levels on BMD measurements at forearm, femoral neck and lumbar spine were not statistically supported by MR analyses. Although causal effect of ADAMTS5 on heel BMD given by the primary MR analysis (ß = -0.006, -0.010 to 0.002, P = 0.004) failed to reach Bonferroni-corrected significance, additional MR approaches and sensitivity analyses indicated a robust causal relationship. CONCLUSION: Our study provided suggestive evidence for the causal effect of higher serum levels of ADAMTS5 on decreased heel BMD, while there was no supportive evidence for the associations of ADAM12, ADAM19, ADAM23, and ADAMTS6 with BMD at forearm, femoral neck and lumbar spine in Europeans.

Genetic relationship between rheumatoid arthritis and cardiovascular diseases : A systematic review of Mendelian randomization studies.

OBJECTIVE: Rheumatoid arthritis (RA) is recognized as a chronic autoimmune disorder with systemic inflammation and joint damage. Its potential role as a risk factor for cardiovascular diseases (CVD) is increasingly noted. This review delves into the causal relationship between RA and CVD, with Mendelian randomization (MR) offering a genetic perspective. METHODS: An extensive search was conducted in PubMed, Cochrane and Web of Science to identify MR studies addressing the RA-CVD link. Out of 530 studies, 9 met the inclusion criteria, which were rigorously assessed using a critical appraisal checklist. These were further stratified by a sensitivity analysis into categories reflecting the strength of their evidence, from not evaluable to robust. RESULTS: From the nine included studies, eight supported a causal association between RA and an increased risk of CVD, specifically coronary artery disease (CAD) and one did not support a link between RA and heart failure. The results suggest that genetic factors associated with RA may contribute to an elevated risk for CVD. Chronic inflammation, prevalent in RA, emerges as a key mediator in this connection. CONCLUSION: The systematic review corroborates a genetic causal link between RA and CVD, as evidenced by eight of the nine MR studies reviewed. This suggests a need for integrated cardiovascular risk management in the treatment of RA patients. The findings advocate considering anti-inflammatory treatment that can reduce cardiovascular risk. The overarching evidence signifies a potential direction for new therapeutic strategies aimed at enhancing cardiovascular health in RA patients.

From Gregor Mendel to Eric Davidson: Mathematical Models and Basic Principles in Biology.

Mathematical models have been widespread in biology since its emergence as a modern experimental science in the 19th century. Focusing on models in developmental biology and heredity, this article (1) presents the properties and epistemological basis of pertinent mathematical models in biology from Mendel's model of heredity in the 19th century to Eric Davidson's model of developmental gene regulatory networks in the 21st; (2) shows that the models differ not only in their epistemologies but also in regard to explicitly or implicitly taking into account basic biological principles, in particular those of biological specificity (that became, in part, replaced by genetic information) and genetic causality. The article claims that models disregarding these principles did not impact the direction of biological research in a lasting way, although some of them, such as D'Arcy Thompson's models of biological form, were widely read and admired and others, such as Turing's models of development, stimulated research in other fields. Moreover, it suggests that successful models were not purely mathematical descriptions or simulations of biological phenomena but were based on inductive, as well as hypothetico-deductive, methodology. The recent availability of large amounts of sequencing data and new computational methodology tremendously facilitates system approaches and pattern recognition in many fields of research. Although these new technologies have given rise to claims that correlation is replacing experimentation and causal analysis, the article argues that the inductive and hypothetico-deductive experimental methodologies have remained fundamentally important as long as causal-mechanistic explanations of complex systems are pursued.