The Omnicausal Model Reveals the Highly Polyfactorial Nature of Complex Diseases [0.03%]
omnicausal模型揭示复杂疾病的多因素性质
Carla Márquez-Luna,Martin Tournaire,Ghislain Rocheleau et al.
Carla Márquez-Luna et al.
Mendelian randomization (MR) is a human genetics method for inferring causal relationships between risk factors and diseases. A common focus of MR studies has been on the causal inference of a single risk factor on a single disease. This ha...
Applying Bayesian Multivariable Mendelian Randomisation to Prioritise Candidate Causal Traits From High-Dimensional Data: Illustration From Estimation of the Effect of Maternal Metabolites on Offspring Birthweight [0.03%]
应用Bayesian多变量孟德尔随机化优先筛选高维数据中的候选因果特征：来自估计母体代谢物对后代出生体重的影响的说明性研究
Ciarrah-Jane Barry,Verena Zuber,Deborah A Lawlor et al.
Ciarrah-Jane Barry et al.
Mendelian randomisation (MR) is an approach to causal inference that uses genetic variants to infer whether or not a causal effect exists, unbiased by unobserved confounding. MR estimation usually considers the effect of a single exposure o...
Individualized Bayesian Inference Identifies Novel Genetic Variants for Parkinson's Disease [0.03%]
个体化贝叶斯推理识别出帕金森病的新遗传变异
Jin Ren,Yasaman J Soofi,Md Asad Rahman et al.
Jin Ren et al.
Parkinson's disease (PD) is a complex neurodegenerative disorder with a significant genetic component. While genome-wide association studies (GWAS) have been instrumental in identifying genetic variants associated with PD, the reliance on l...
DRIVE v3: Command Line Application for Identity-by-Descent Haplotype Clustering in Large Biobank Scale Data [0.03%]
DRIVE v3：大型生物银行规模数据身份同源单倍型聚类的命令行应用程序
James T Baker,Hung-Hsin Chen,Grahame F Evans et al.
James T Baker et al.
There is a need for genetic analytical methods that integrate multi-individual identity-by-descent (IBD) tools with phenotypic enrichment testing to discover novel shared haplotypes contributing to disease traits. Existing tools are designe...
Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics [0.03%]
深度无监督领域自适应在将癌细胞系依赖性图谱转换为乳腺肿瘤基因组学中的应用
Yu Shi,Wei Xu,Pingzhao Hu
Yu Shi
The Cancer dependency maps (DepMap) identify genetic dependencies in cancer cells using large-scale loss-of-function screens, providing a foundation for cancer-specific treatment strategies. However, discrepancies exist between cancer cell ...
Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis [0.03%]
动脉粥样硬化多元民族研究中发生的痴呆的多基因风险评分
Diane Xue,Elizabeth E Blue,Tamar Sofer et al.
Diane Xue et al.
Over 75 Alzheimer's disease (AD) and dementia-associated variants have been identified through genome-wide association studies, but the utility of polygenic risk scores (PRS) for predicting AD and dementia in diverse and admixed populations...
Outcome and Exposure Polygenic Risk Scores Can Help Reduce Information Bias and Selection Bias in Regression Estimates From Biobank Data [0.03%]
利用生物样本库数据减少回归估计的信息偏差和选择偏差的结果和暴露多基因风险评分
Maxwell Salvatore,Ritoban Kundu,Jiacong Du et al.
Maxwell Salvatore et al.
Electronic health records (EHRs) are valuable sources of data but are susceptible to biases from missing data and sample selection, often due to clinically informative visiting processes and non-probability sampling. This research explores ...
Comment on: A Novel Mendelian Randomization Method With Binary Risk Factor and Outcome [0.03%]
关于二分类风险因素和结果的新型孟德尔随机化方法的点评
Sandeep Chowdary Vejandla,Mengchen Ding,Hemant K Tiwari
Sandeep Chowdary Vejandla
Shared and Distinct Genetic Factors Underlying Bile Acid Regulation and Intrahepatic Cholestasis of Pregnancy [0.03%]
胆汁酸调节和妊娠期肝内胆汁淤积症共有的和独特的遗传因素
Xinyi Zhang,Junwei Li,Huanhuan Zhu et al.
Xinyi Zhang et al.
Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder characterized by elevated total bile acid (TBA) levels, leading to adverse maternal and fetal outcomes. While genetic factors contribute to ICP and bile acid...
Meta-Analysis
Genetic epidemiology. 2026 Jun;50(4):e70040. DOI:10.1002/gepi.70040 2026
Evaluating a Mendelian Risk Prediction Model That Aggregates Across Genes and Cancers [0.03%]
一种能在基因和癌症之间进行汇聚评估的美登氏风险预测模型的研究
Jane W Liang,Gregory E Idos,Christine Hong et al.
Jane W Liang et al.
Using principles of Mendelian genetics, probability theory, and mutation-specific knowledge, Mendelian risk prediction models identify those at high risk of carrying a heritable cancer susceptibility variant and assess future risk of cancer...