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<p>Alzheimer’s disease (AD) is an age-related neurodegenerative disorder characterized by insidious and gradual onset. Identifying biomarkers associated with the early stages of AD is crucial for delaying its progression. In this study, we aimed to identify AD-related biomarkers in blood and urine by integrating genetic correlation analysis, shared genetic loci identification, and causal inference using linkage disequilibrium score regression (LDSC), conjunction false discovery rate (conjFDR), generalized summary data-based Mendelian randomization (GSMR) and two-sample Mendelian randomization (MR). To enhance robustness and minimize sample bias, we cross-validated findings using different AD GWAS datasets. Across multiple AD GWASs, we consistently observed nominally significant genetic correlations: AD was positively correlated with albumin (ALB) and negatively correlated with cystatin C (CYS) and urea (BUN). MR analysis further suggested that genetic predisposition to higher level of ALB and lower level of non-albumin protein (NAP) can represent risk factors for AD. In reverse MR analysis, a higher genetic risk for AD can predispose individuals to higher levels of ratio of aspartate aminotransferase to alanine aminotransferase (AST2ALT) and estimated glomerular filtration rate (EGFR), as well as lower level of creatinine (CRE). Overall, this study provides insights into the genetic correlations and causal relationships between AD and several biomarkers, offering potential candidates for AD diagnosis and management.</p>

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Genetic Correlations and Causalities between Alzheimer’s Disease and 35 Biomarkers in Blood and Urine

  • 期刊论文

  • 发表日期：

    2025年4月25日

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  • Sheng Zhang,
  • Yu-Lin Yao,
  • Yichen Li,
  • Xiaofan Zhang,
  • Yong Wu

摘要

Alzheimer’s disease (AD) is an age-related neurodegenerative disorder characterized by insidious and gradual onset. Identifying biomarkers associated with the early stages of AD is crucial for delaying its progression. In this study, we aimed to identify AD-related biomarkers in blood and urine by integrating genetic correlation analysis, shared genetic loci identification, and causal inference using linkage disequilibrium score regression (LDSC), conjunction false discovery rate (conjFDR), generalized summary data-based Mendelian randomization (GSMR) and two-sample Mendelian randomization (MR). To enhance robustness and minimize sample bias, we cross-validated findings using different AD GWAS datasets. Across multiple AD GWASs, we consistently observed nominally significant genetic correlations: AD was positively correlated with albumin (ALB) and negatively correlated with cystatin C (CYS) and urea (BUN). MR analysis further suggested that genetic predisposition to higher level of ALB and lower level of non-albumin protein (NAP) can represent risk factors for AD. In reverse MR analysis, a higher genetic risk for AD can predispose individuals to higher levels of ratio of aspartate aminotransferase to alanine aminotransferase (AST2ALT) and estimated glomerular filtration rate (EGFR), as well as lower level of creatinine (CRE). Overall, this study provides insights into the genetic correlations and causal relationships between AD and several biomarkers, offering potential candidates for AD diagnosis and management.