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Results for “posterior odds of causality”

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BICEP: Bayesian inference for rare genomic variant causality evaluation in pedigrees.

Next-generation sequencing is widely applied to the investigation of pedigree data for gene discovery. However, identifying plausible disease-causing variants within a robust statistical framework is challenging. Here, we introduce BICEP: a Bayesian inference tool for rare variant causality evaluation in pedigree-based cohorts. BICEP calculates the posterior odds that a genomic variant is causal for a phenotype based on the variant cosegregation as well as a priori evidence such as deleteriousness and functional consequence. BICEP can correctly identify causal variants for phenotypes with both Mendelian and complex genetic architectures, outperforming existing methodologies. Additionally, BICEP can correctly down-weight common variants that are unlikely to be involved in phenotypic liability in the context of a pedigree, even if they have reasonable cosegregation patterns. The output metrics from BICEP allow for the quantitative comparison of variant causality within and across pedigrees, which is not possible with existing approaches.

Pedigree

Bayesian Mendelian randomization reveals a protective effect of later age at first sexual intercourse against erectile dysfunction.

Erectile dysfunction (ED) is a prevalent health condition with significant psychosocial impacts, yet the causal role of age at first sexual intercourse (AFS) remains unclear. This study investigated the causal effect of AFS on the risk of ED using Mendelian randomization (MR) and Bayesian methods. Five traditional 2-sample MR analyses and 5 Bayesian MR analyses were performed using genome-wide association studies summary statistics from European populations. Sensitivity analyses included MR Egger regression, MR-pleiotropy residual sum and outlier, and Cochran Q-test. In mixed-sex cohorts (Groups 1 and 2), inverse variance weighted results demonstrated significant protective effects: odds ratio (OR) = 0.626, θ = -0.469, P = 2.73 × 10-6 for Group 1 and OR = 0.617, θ = -0.483, P = 3.56 × 10-5 for Group 2. The analyses for male-specific cohorts (Groups 3-10) showed weaker but consistent effects. For Group 3, OR = 0.643, θ = -0.442, P = .010. For Group 4, some instrumental variables associated with confounders were removed. The result became statistically insignificant: OR = 0.680, θ = -0.385, P = .064. For Group 5, the instrument selection criteria were relaxed and significance was retained: OR = 0.695, θ = -0.364, P = .016. For Groups 6 to 10, Bayesian MR was used to strengthen the inferences. In particular, for Group 8, which has a strongly informed prior, a posterior mean θ = -0.358 and a 95% credible interval (-0.575, -0.136) were obtained. This study provides evidence supporting a causal protective effect of later AFS on ED risk. While traditional MR analyses in male-specific cohorts yielded suggestive results, Bayesian MR analyses, which allow for the integration of prior evidence, provided more precise estimates and strengthened the causal inference. These findings may inform future sexual health policies. Strengths include the use of male-specific cohorts and Bayesian enhancement for weak instruments. Limitations include reliance on European-ancestry data and inability to stratify ED subtypes.

Male

Circulating inflammatory proteins and osteomyelitis: A bidirectional Mendelian randomization and colocalization analysis.

Circulating inflammatory proteins (CIPs) have been implicated in the progression of osteomyelitis (OM); however, whether these proteins play a causal role or are merely a consequence remains unclear. This study aimed to assess the causal relationships between CIPs and OM using a bidirectional 2-sample Mendelian randomization (MR) approach. MR analyses were performed using genome-wide association study summary statistics for 91 inflammation-related proteins (n&#x2005;=&#x2005;14,824) and OM (1881 cases and 3,91,037 controls). The inverse variance weighted method was used as the primary analytical approach, supplemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analyses were conducted to evaluate heterogeneity, horizontal pleiotropy, and robustness. Colocalization analysis was applied to identify shared causal variants, and pathway enrichment analysis was used to explore underlying biological mechanisms. Forward MR analysis revealed that elevated levels of tumor necrosis factor-beta (TNF-&#x3b2;) were significantly associated with increased OM risk (odds ratio [OR]&#x2005;=&#x2005;1.132; 95% confidence interval [CI]: 1.052-1.217; false discovery rate [FDR]&#x2005;=&#x2005;0.027). Conversely, decreased levels of osteoprotegerin (OR&#x2005;=&#x2005;0.772; 95% CI: 0.671-0.889; FDR&#x2005;=&#x2005;0.015) and adenosine deaminase (OR&#x2005;=&#x2005;0.811; 95% CI: 0.736-0.894; FDR&#x2005;<&#x2005;0.001) were associated with increased OM risk. Reverse MR analysis identified increased levels of interleukin-15 receptor alpha, C-X-C motif chemokine ligand 1, fms-related tyrosine kinase 3 ligand, interleukin-20, interleukin-10 (IL10), C-C motif chemokine ligand 19, and CXCL6 as being significantly associated with OM susceptibility (all FDR&#x2005;<&#x2005;0.05). Colocalization analysis provided strong evidence for a shared causal variant between TNF-&#x3b2; and OM (posterior probability for hypothesis 4&#x2005;=&#x2005;0.999). Enrichment analyses indicated involvement of implicated proteins in Toll-like receptor signaling and T-helper 17 cell differentiation pathways. This study identified several CIPs - including TNF-&#x3b2;, osteoprotegerin, and adenosine deaminase - as potentially causal in OM development. These findings highlight promising targets for future immunomodulatory therapies aimed at preventing or mitigating osteomyelitis.

Humans