Objective: This study aims to examine the causal relationship between inflammatory factors and the probability of developing vascular dementia (VD) using Mendelian Randomization (MR) and Chinese herbal medicine predic...Objective: This study aims to examine the causal relationship between inflammatory factors and the probability of developing vascular dementia (VD) using Mendelian Randomization (MR) and Chinese herbal medicine prediction method, and to screen potential Chinese herbal medicines for the prevention and treatment of VD. Methods: Single nucleotide polymorphisms (SNPs) that exhibit a strong association with vascular dementia (VD) were identified as instrumental variables from the summary statistics of genome-wide association studies (GWAS). The primary analytical method employed was inverse variance weighting (IVW), while auxiliary analyses included the MR-Egger method, weighted median method, simple model, and weighted model. A two-way Mendelian randomization analysis was conducted to assess the causal relationship between inflammatory factors and the risk of VD, thereby identifying the key inflammatory factors involved. The MR-Egger intercept test and Cochran’s Q test were employed to assess the horizontal polymorphism and heterogeneity of instrumental variables. A sensitivity analysis was conducted by excluding one method at a time. Ultimately, based on key inflammatory factors, predictions for the prevention and treatment using traditional Chinese medicine were made, along with the screening of homologous herbal remedies. Results: Based on the results of the forward MR, the probability of developing VD was elevated when the inflammatory factors CXCL10 and CXCL5 were expressed at higher levels, whereas the probability of developing VD decreased as the expression levels of IL-13 and IL-20RA increased. These findings were supported by the assessment of pleiotropy, heterogeneity, and sensitivity. The results of the reverse MR analysis showed that there was no causal relationship between VD, as an exposure dataset, and these four inflammatory factors. According to the key inflammatory factors, 37 Chinese herbal medicines such as Siraitia grosvenorii were selected. Their characteristics including four natures, five flavors, channel tropism and treatment efficiency were cold, warm, neutral, pungent, sweet, bitter, lung meridian, spleen meridian, liver meridian, kidney meridian and clearing heat. Among them, Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi were all medicine and food homologous Chinese herbal medicines. Conclusions: The increase of CXCL10 and CXCL5 expression levels can increase the risk of VD, and the increase of IL-13 and IL-20 RA expression levels can reduce the risk of VD. Siraitia grosvenorii and other Chinese herbal medicines might be potential sources of therapeutic drugs for the treatment of VD. Medicine and food homologous Chinese herbal medicines, such as Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi, may help the elderly population with corresponding Traditional Chinese Medicine (TCM) constitutions to prevent VD.展开更多
People learn causal relations since childhood using counterfactual reasoning. Counterfactual reasoning uses counterfactual examples which take the form of “what if this has happened differently”. Counterfactual exam...People learn causal relations since childhood using counterfactual reasoning. Counterfactual reasoning uses counterfactual examples which take the form of “what if this has happened differently”. Counterfactual examples are also the basis of counterfactual explanation in explainable artificial intelligence (XAI). However, a framework that relies solely on optimization algorithms to find and present counterfactual samples cannot help users gain a deeper understanding of the system. Without a way to verify their understanding, the users can even be misled by such explanations. Such limitations can be overcome through an interactive and iterative framework that allows the users to explore their desired “what-if” scenarios. The purpose of our research is to develop such a framework. In this paper, we present our “what-if” XAI framework (WiXAI), which visualizes the artificial intelligence (AI) classification model from the perspective of the user’s sample and guides their “what-if” exploration. We also formulated how to use the WiXAI framework to generate counterfactuals and understand the feature-feature and feature-output relations in-depth for a local sample. These relations help move the users toward causal understanding.展开更多
背景:骨质疏松性骨折是骨质疏松症最严重的并发症,既往的研究已经证实了肠道菌群对骨骼组织具有调节作用,肠道菌群与骨质疏松性骨折有着重要关系,但是二者之间的因果关系尚不清楚。目的:使用孟德尔随机化(MR)方法探索肠道菌群与骨质疏...背景:骨质疏松性骨折是骨质疏松症最严重的并发症,既往的研究已经证实了肠道菌群对骨骼组织具有调节作用,肠道菌群与骨质疏松性骨折有着重要关系,但是二者之间的因果关系尚不清楚。目的:使用孟德尔随机化(MR)方法探索肠道菌群与骨质疏松性骨折之间的因果关系。方法:从IEU Open GWAS数据库和芬兰数据库R9中分别获得了肠道菌群和骨质疏松性骨折的GWAS数据集,以肠道菌群作为暴露因素,骨质疏松性骨折作为结局变量,采用随机效应逆方差加权法、MR-Egger回归、加权中位数法、简单模型法以及加权模型法进行孟德尔随机化分析来评估肠道菌群与骨质疏松性骨折之间是否存在因果关系,通过敏感性分析来检验结果的可靠性和稳健性,并进行反向孟德尔随机化分析来进一步验证正向孟德尔随机化分析中确定的因果关系。结果与结论:①此孟德尔随机化分析结果表明,肠道菌群与骨质疏松性骨折之间存在因果关系。放线菌目(OR=1.562,95%CI:1.027-2.375,P=0.037)、放线菌科(OR=1.561,95%CI:1.027-2.374,P=0.037)、放线菌属(OR=1.544,95%CI:1.130-2.110,P=0.006)、丁酸球菌属(OR=1.781,95%CI:1.194-2.657,P=0.005)、粪球菌属-2(OR=1.550,95%CI:1.068-2.251,P=0.021)、Family ⅩⅢ UCG-001属(OR=1.473,95%CI:1.001-2.168,P=0.049)、产甲烷短杆菌属(OR=1.274,95%CI:1.001-1.621,P=0.049)、罗氏菌属(OR=1.429,95%CI:1.015-2.013,P=0.041)的丰度升高,会增加患者骨质疏松性骨折的风险;②拟杆菌纲(OR=0.660,95%CI:0.455-0.959,P=0.029)、拟杆菌目(OR=0.660,95%CI:0.455-0.959,P=0.029)、克里斯滕森氏菌科(OR=0.725,95%CI:0.529-0.995,P=0.047)、瘤胃球菌科(OR=0.643,95%CI:0.443-0.933,P=0.020)、肠杆菌属(OR=0.558,95%CI:0.395-0.788,P=0.001)、直肠真杆菌属(OR=0.631,95%CI:0.435-0.916,P=0.016)、毛螺菌科-UCG008(OR=0.738,95%CI:0.546-0.998,P=0.048)、瘤胃梭菌属-9(OR=0.492,95%CI:0.324-0.746,P=0.001)的丰度升高,会降低患者骨质疏松性骨折的风险。③文章通过孟德尔随机化方法发现了16种与骨质疏松性骨折相关的肠道菌群,即以肠道菌群为暴露因素,骨质疏松性骨折为结局变量,8种肠道菌群与骨质疏松性骨折呈正向因果关联,另外8种肠道菌群与骨质疏松性骨折呈负向因果关联。④此研究结果不仅为临床上骨质疏松性骨折的早期预测及潜在治疗靶点确定了新的生物标志物,还为骨组织工程中研究通过肠道菌群改善骨质疏松性骨折的发生与预后提供了实验基础和理论依据。展开更多
背景:膝骨关节炎是一种常见的关节软骨及周围组织损伤的慢性炎症性疾病,而免疫细胞在膝骨关节炎免疫炎症反应中起到重要作用,但其中的具体机制仍有待深入研究。目的:采用孟德尔随机化方法来评估731种免疫细胞表型与膝骨关节炎风险之间...背景:膝骨关节炎是一种常见的关节软骨及周围组织损伤的慢性炎症性疾病,而免疫细胞在膝骨关节炎免疫炎症反应中起到重要作用,但其中的具体机制仍有待深入研究。目的:采用孟德尔随机化方法来评估731种免疫细胞表型与膝骨关节炎风险之间的潜在因果关系。方法:使用全基因组关联分析(GWAS)目录中公开获取731种免疫细胞表型的全基因组关联分析统计数据(从GCST0001391到GCST0002121)和IEUGWAS数据库中膝骨关节炎的全基因组关联分析数据(ebi-a-GCST007090)。采用逆方差加权法、MR-Egger回归法、加权中位数法、加权模型法和简单模型法来研究免疫细胞与膝骨关节炎之间的因果关系。敏感性分析用于检验孟德尔随机化分析结果是否可靠,然后以同样方法进行反向孟德尔随机化分析。结果与结论:①正向分析结果表明,共有4种免疫细胞表型与膝骨关节炎有显著的因果关系(FDR<0.20),其中B细胞中的CD27 on CD24+CD27+(OR=1.026,P=0.00026,Pfdr=0.18)、髓系细胞中的CD33 on CD33dim HLA DR-(OR=1.014,P=0.00050,Pfdr=0.18)以及Treg细胞中的CD45RA+CD28-CD8br%CD8br(OR=1.001,P=0.00078,Pfdr=0.18)与膝骨关节炎风险呈直接的正向因果关联;单核细胞中PDL-1 on monocyte(OR=0.952,P=0.00098,Pfdr=0.18)与膝骨关节炎风险呈直接的负向因果关联。②反向分析结果表明,当膝骨关节炎作为暴露数据时,与731种免疫细胞表型均不具有显著因果关系(FDR<0.20)。③敏感性分析结果显示:双向孟德尔随机化的Cochran’s Q检验和MR-Egger回归法结果P值均大于0.05,表明免疫细胞表型与膝骨关节炎之间的因果效应分析不存在显著的异质性和多效性。④上述结果证实,CD27 on CD24+CD27+,CD33 on CD33dim HLA DR-,CD45RA+CD28-CD8br%CD8br以及PDL-1 on monocyte免疫细胞表型与膝骨关节炎之间可能具有较为显著的潜在因果关系,这为研究膝骨关节炎的生物学机制及探索膝骨关节炎的早期防治提供有价值的线索,也为干预性药物的开发提供了新的方向。展开更多
文摘Objective: This study aims to examine the causal relationship between inflammatory factors and the probability of developing vascular dementia (VD) using Mendelian Randomization (MR) and Chinese herbal medicine prediction method, and to screen potential Chinese herbal medicines for the prevention and treatment of VD. Methods: Single nucleotide polymorphisms (SNPs) that exhibit a strong association with vascular dementia (VD) were identified as instrumental variables from the summary statistics of genome-wide association studies (GWAS). The primary analytical method employed was inverse variance weighting (IVW), while auxiliary analyses included the MR-Egger method, weighted median method, simple model, and weighted model. A two-way Mendelian randomization analysis was conducted to assess the causal relationship between inflammatory factors and the risk of VD, thereby identifying the key inflammatory factors involved. The MR-Egger intercept test and Cochran’s Q test were employed to assess the horizontal polymorphism and heterogeneity of instrumental variables. A sensitivity analysis was conducted by excluding one method at a time. Ultimately, based on key inflammatory factors, predictions for the prevention and treatment using traditional Chinese medicine were made, along with the screening of homologous herbal remedies. Results: Based on the results of the forward MR, the probability of developing VD was elevated when the inflammatory factors CXCL10 and CXCL5 were expressed at higher levels, whereas the probability of developing VD decreased as the expression levels of IL-13 and IL-20RA increased. These findings were supported by the assessment of pleiotropy, heterogeneity, and sensitivity. The results of the reverse MR analysis showed that there was no causal relationship between VD, as an exposure dataset, and these four inflammatory factors. According to the key inflammatory factors, 37 Chinese herbal medicines such as Siraitia grosvenorii were selected. Their characteristics including four natures, five flavors, channel tropism and treatment efficiency were cold, warm, neutral, pungent, sweet, bitter, lung meridian, spleen meridian, liver meridian, kidney meridian and clearing heat. Among them, Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi were all medicine and food homologous Chinese herbal medicines. Conclusions: The increase of CXCL10 and CXCL5 expression levels can increase the risk of VD, and the increase of IL-13 and IL-20 RA expression levels can reduce the risk of VD. Siraitia grosvenorii and other Chinese herbal medicines might be potential sources of therapeutic drugs for the treatment of VD. Medicine and food homologous Chinese herbal medicines, such as Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi, may help the elderly population with corresponding Traditional Chinese Medicine (TCM) constitutions to prevent VD.
文摘People learn causal relations since childhood using counterfactual reasoning. Counterfactual reasoning uses counterfactual examples which take the form of “what if this has happened differently”. Counterfactual examples are also the basis of counterfactual explanation in explainable artificial intelligence (XAI). However, a framework that relies solely on optimization algorithms to find and present counterfactual samples cannot help users gain a deeper understanding of the system. Without a way to verify their understanding, the users can even be misled by such explanations. Such limitations can be overcome through an interactive and iterative framework that allows the users to explore their desired “what-if” scenarios. The purpose of our research is to develop such a framework. In this paper, we present our “what-if” XAI framework (WiXAI), which visualizes the artificial intelligence (AI) classification model from the perspective of the user’s sample and guides their “what-if” exploration. We also formulated how to use the WiXAI framework to generate counterfactuals and understand the feature-feature and feature-output relations in-depth for a local sample. These relations help move the users toward causal understanding.
文摘背景:骨质疏松性骨折是骨质疏松症最严重的并发症,既往的研究已经证实了肠道菌群对骨骼组织具有调节作用,肠道菌群与骨质疏松性骨折有着重要关系,但是二者之间的因果关系尚不清楚。目的:使用孟德尔随机化(MR)方法探索肠道菌群与骨质疏松性骨折之间的因果关系。方法:从IEU Open GWAS数据库和芬兰数据库R9中分别获得了肠道菌群和骨质疏松性骨折的GWAS数据集,以肠道菌群作为暴露因素,骨质疏松性骨折作为结局变量,采用随机效应逆方差加权法、MR-Egger回归、加权中位数法、简单模型法以及加权模型法进行孟德尔随机化分析来评估肠道菌群与骨质疏松性骨折之间是否存在因果关系,通过敏感性分析来检验结果的可靠性和稳健性,并进行反向孟德尔随机化分析来进一步验证正向孟德尔随机化分析中确定的因果关系。结果与结论:①此孟德尔随机化分析结果表明,肠道菌群与骨质疏松性骨折之间存在因果关系。放线菌目(OR=1.562,95%CI:1.027-2.375,P=0.037)、放线菌科(OR=1.561,95%CI:1.027-2.374,P=0.037)、放线菌属(OR=1.544,95%CI:1.130-2.110,P=0.006)、丁酸球菌属(OR=1.781,95%CI:1.194-2.657,P=0.005)、粪球菌属-2(OR=1.550,95%CI:1.068-2.251,P=0.021)、Family ⅩⅢ UCG-001属(OR=1.473,95%CI:1.001-2.168,P=0.049)、产甲烷短杆菌属(OR=1.274,95%CI:1.001-1.621,P=0.049)、罗氏菌属(OR=1.429,95%CI:1.015-2.013,P=0.041)的丰度升高,会增加患者骨质疏松性骨折的风险;②拟杆菌纲(OR=0.660,95%CI:0.455-0.959,P=0.029)、拟杆菌目(OR=0.660,95%CI:0.455-0.959,P=0.029)、克里斯滕森氏菌科(OR=0.725,95%CI:0.529-0.995,P=0.047)、瘤胃球菌科(OR=0.643,95%CI:0.443-0.933,P=0.020)、肠杆菌属(OR=0.558,95%CI:0.395-0.788,P=0.001)、直肠真杆菌属(OR=0.631,95%CI:0.435-0.916,P=0.016)、毛螺菌科-UCG008(OR=0.738,95%CI:0.546-0.998,P=0.048)、瘤胃梭菌属-9(OR=0.492,95%CI:0.324-0.746,P=0.001)的丰度升高,会降低患者骨质疏松性骨折的风险。③文章通过孟德尔随机化方法发现了16种与骨质疏松性骨折相关的肠道菌群,即以肠道菌群为暴露因素,骨质疏松性骨折为结局变量,8种肠道菌群与骨质疏松性骨折呈正向因果关联,另外8种肠道菌群与骨质疏松性骨折呈负向因果关联。④此研究结果不仅为临床上骨质疏松性骨折的早期预测及潜在治疗靶点确定了新的生物标志物,还为骨组织工程中研究通过肠道菌群改善骨质疏松性骨折的发生与预后提供了实验基础和理论依据。
文摘背景:膝骨关节炎是一种常见的关节软骨及周围组织损伤的慢性炎症性疾病,而免疫细胞在膝骨关节炎免疫炎症反应中起到重要作用,但其中的具体机制仍有待深入研究。目的:采用孟德尔随机化方法来评估731种免疫细胞表型与膝骨关节炎风险之间的潜在因果关系。方法:使用全基因组关联分析(GWAS)目录中公开获取731种免疫细胞表型的全基因组关联分析统计数据(从GCST0001391到GCST0002121)和IEUGWAS数据库中膝骨关节炎的全基因组关联分析数据(ebi-a-GCST007090)。采用逆方差加权法、MR-Egger回归法、加权中位数法、加权模型法和简单模型法来研究免疫细胞与膝骨关节炎之间的因果关系。敏感性分析用于检验孟德尔随机化分析结果是否可靠,然后以同样方法进行反向孟德尔随机化分析。结果与结论:①正向分析结果表明,共有4种免疫细胞表型与膝骨关节炎有显著的因果关系(FDR<0.20),其中B细胞中的CD27 on CD24+CD27+(OR=1.026,P=0.00026,Pfdr=0.18)、髓系细胞中的CD33 on CD33dim HLA DR-(OR=1.014,P=0.00050,Pfdr=0.18)以及Treg细胞中的CD45RA+CD28-CD8br%CD8br(OR=1.001,P=0.00078,Pfdr=0.18)与膝骨关节炎风险呈直接的正向因果关联;单核细胞中PDL-1 on monocyte(OR=0.952,P=0.00098,Pfdr=0.18)与膝骨关节炎风险呈直接的负向因果关联。②反向分析结果表明,当膝骨关节炎作为暴露数据时,与731种免疫细胞表型均不具有显著因果关系(FDR<0.20)。③敏感性分析结果显示:双向孟德尔随机化的Cochran’s Q检验和MR-Egger回归法结果P值均大于0.05,表明免疫细胞表型与膝骨关节炎之间的因果效应分析不存在显著的异质性和多效性。④上述结果证实,CD27 on CD24+CD27+,CD33 on CD33dim HLA DR-,CD45RA+CD28-CD8br%CD8br以及PDL-1 on monocyte免疫细胞表型与膝骨关节炎之间可能具有较为显著的潜在因果关系,这为研究膝骨关节炎的生物学机制及探索膝骨关节炎的早期防治提供有价值的线索,也为干预性药物的开发提供了新的方向。
