Investigating genetic links between blood metabolites and preeclampsia
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ABSTRACT:
SUBMITTER: Lin Q
PROVIDER: S-EPMC10996307 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundIdentifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD).MethodsFollowing quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (pFDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (pFDR < 0.05) with an imaging outcome (N = 1638).ResultsIn the fully adjusted model, three lipid modules were associated with a brain volume measure (pFDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß = - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß = - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (pFDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction.ConclusionsOur findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.
| S-EPMC9945600 | biostudies-literature
Project description:Preeclampsia and eclampsia are serious complications of pregnancy, leading to high rates of maternal and neonatal mortality. During pregnancy, there are changes in relevant serum metabolites in women. However, it remains unclear if these serum metabolites contribute to the development of associated disorders during pregnancy. Therefore, we conducted a Mendelian randomization study to explore the causal relationship between serum metabolites and preeclampsia and eclampsia. We utilized the inverse variance weighted model as our primary analysis approach. We complemented this with sensitivity analyses, including the heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis, to ensure the robustness of our findings. Furthermore, we conducted linkage disequilibrium score regression, multivariable Mendelian randomization, and metabolic pathway analysis to further explore the genetic data. The Mendelian randomization analysis has identified γ-glutamylglutamine, inosine, and isoleucine 10 metabolites that are significantly associated with preeclampsia, and γ-glutamylglutamine and phenylacetate 8 metabolites that may potentially contribute to the development of eclampsia. Notably, γ-glutamylglutamine has been found to have a causal relationship with both preeclampsia and eclampsia. In the multivariable Mendelian randomization analysis, our research findings suggest that both isoleucine and X-14304-leucylalanine directly impact preeclampsia within the context of amino acids and peptides. Moreover, our observations reveal that carbohydrates can also have a direct effect on preeclampsia. Importantly, it should be emphasized that only 3-lactate in amino acids has been shown to have a direct influence on eclampsia. This research has the potential to enhance our understanding of the biological variances related to disease status, providing a foundation for future investigations.
| S-EPMC10977518 | biostudies-literature
Project description:ObjectiveThis study aimed to explore the potential causal relationship between the gut microbiota and/or its metabolites and the progression of chronic hepatitis B (CHB).MethodThe gut microbiota was used as the exposure factor. The training set exposure data were obtained from the China Nucleotide Sequence Archive (CNSA). Genome-wide association study (GWAS) data from Asia were used as the outcome variables. Outcome data for both the training and validation sets were sourced from the GWAS Catalog database. A dual-sample Mendelian randomization approach was used to analyze the causal relationships, with the inverse variance-weighted method serving as the main analytical strategy. Sensitivity analysis was conducted to assess the robustness of Mendelian randomization analysis results.ResultIn the training set database, analysis using the inverse variance-weighted method revealed a positive correlation between Fusobacterium varium and chronic hepatitis B [OR = 1.122, 95% CI (1.016, 1.240), p = 0.022]. Conversely, Veillonella parvula exhibited a negative correlation with chronic hepatitis B [OR = 0.917, 95% CI (0.852, 0.987), p = 0.021]. Sensitivity analysis revealed no evidence of pleiotropy and heterogeneity. No gut microbiota metabolites with a causal effect on chronic hepatitis B were identified. Additionally, no associations between the gut microbiota and the progression of chronic hepatitis B were found in the validation data from the European cohort.ConclusionThis study suggests that F. varium may facilitate the progression of chronic hepatitis B, whereas V. parvula may impede it. No causal relationships between gut microbiota metabolites and chronic hepatitis B were established.
| S-EPMC11303287 | biostudies-literature
Project description:The availability of genome-wide association studies (GWASs) for human blood metabolome provides an excellent opportunity for studying metabolism in a heritable disease such as migraine. Utilizing GWAS summary statistics, we conduct comprehensive pairwise genetic analyses to estimate polygenic genetic overlap and causality between 316 unique blood metabolite levels and migraine risk. We find significant genome-wide genetic overlap between migraine and 44 metabolites, mostly lipid and organic acid metabolic traits (FDR < 0.05). We also identify 36 metabolites, mostly related to lipoproteins, that have shared genetic influences with migraine at eight independent genomic loci (posterior probability > 0.9) across chromosomes 3, 5, 6, 9, and 16. The observed relationships between genetic factors influencing blood metabolite levels and genetic risk for migraine suggest an alteration of metabolite levels in individuals with migraine. Our analyses suggest higher levels of fatty acids, except docosahexaenoic acid (DHA), a very long-chain omega-3, in individuals with migraine. Consistently, we found a causally protective role for a longer length of fatty acids against migraine. We also identified a causal effect for a higher level of a lysophosphatidylethanolamine, LPE(20:4), on migraine, thus introducing LPE(20:4) as a potential therapeutic target for migraine.
| S-EPMC8595896 | biostudies-literature
Project description:ObjectivePreeclampsia is a complex genetic disease of pregnancy with a heterogenous presentation, unknown cause and potential severe outcomes for both mother and child. Preeclamptic women have increased risk for atherothrombotic cardiovascular disease. We aimed to identify heritabilities and phenotypic correlations of preeclampsia and related conditions in the Norwegian Preeclampsia Family Biobank.MethodsBy applying a variance components model, a total of 493 individuals (from 138 families with increased occurrence of preeclampsia) were classified according to 30 disease-related phenotypes.ResultsOf parous women, 75.7% (263/338) had experienced preeclampsia and 35.7% of women with and 22.4% without preeclampsia delivered children small for gestational age (SGA). We identified 11 phenotypes as heritable. The increased occurrence of preeclampsia was reflected by the presence [heritability (H2r)?=?0.60)] and severity (H2r?=?0.15) of preeclampsia and being born in a preeclamptic pregnancy (H2r?=?0.25). Other heritable phenotypes identified included SGA (H2r?=?0.40), chronic hypertension (H2r?=?0.57), severity of atherothrombotic cardiovascular disease (H2r?=?0.31), BMI (H2r?=?0.60) and pulmonary disease (H2r?=?0.91). The heritable phenotype preeclampsia overlapped with SGA (P?=?0.03), whereas pulmonary disease was phenotypically correlated with atherothrombotic cardiovascular disease (P?<?0.01), SGA (P?=?0.02) and BMI (P?=?0.02).ConclusionThis is the first study identifying the H2r of a range of health-related conditions in preeclamptic families. Our study demonstrates how refinement of phenotypes leads to better H2r estimation and the identification of a biological relationship between preeclampsia and related traits.
| S-EPMC4596487 | biostudies-literature
Project description:The aim was to study the genetic correlation and causal relationship between spondyloarthritis (SpA) and blood metabolites based on the large-scale genome-wide association study (GWAS) summary data. The GWAS summary data (3966 SpA and 448,298 control cases) of SpA were from the UK Biobank, and the GWAS summary data (486 blood metabolites) of human blood metabolites were from a published study. First, the genetic correlation between SpA and blood metabolites was analyzed by linkage disequilibrium score (LDSC) regression. Next, we used Mendelian randomization (MR) analysis to perform access causal relationship between SpA and blood metabolites. Random effects inverse variance weighted (IVW) was the main analysis method, and the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The MR analysis results were dominated by the random effects IVW. The Cochran's Q statistic (MR-IVW) and Rucker's Q statistic (MR Egger) were used to check heterogeneity. MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) were used to check horizontal pleiotropy. The MR-PRESSO was also used to check outliers. The "leave-one-out" analysis was used to assess whether the MR analysis results were affected by a single SNP and thus test the robustness of the MR results. Finally, we identified seven blood metabolites that are genetically related to SpA: X-10395 (correlation coefficient = -0.546, p = 0.025), pantothenate (correlation coefficient = -0.565, p = 0.038), caprylate (correlation coefficient = -0.333, p = 0.037), pelargonate (correlation coefficient = -0.339, p = 0.047), X-11317 (correlation coefficient = -0.350, p = 0.038), X-12510 (correlation coefficient = -0.399, p = 0.034), and X-13859 (Correlation coefficient = -0.458, p = 0.015). Among them, X-10395 had a positive genetic causal relationship with SpA (p = 0.014, OR = 1.011). The blood metabolites that have genetic correlation and causal relationship with SpA found in this study provide a new idea for the study of the pathogenesis of SpA and the determination of diagnostic indicators.
| S-EPMC9917834 | biostudies-literature
Project description:BackgroundSeveral recent investigations have posited that distinct metabolites in the bloodstream may be correlated with the pathogenesis of Pulmonary Hypertension (PH). Nonetheless, the interrelationship between the pathogenesis of PH and metabolite fluctuations remains incompletely elucidated, and findings may differ across studies.MethodsIn the extant research, data from 486 metabolite-and PH-related genetic variants in human subjects were procured based on Genome-Wide Association Studies (GWAS) and Finnish databases. Univariate Mendelian Randomization analyses were deployed to evaluate the causal relationships between them. The utilization of the randomized Inverse Variance weighted(IVW) method served as the primary analytic framework in this Mendelian Randomization (MR) study. Additionally, four alternative computational strategies, encompassing MR-Egger, were employed as auxiliary methods. A myriad of tests, including Cochran's Q Test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and linkage disequilibrium score were incorporated to assess the robustness of the study outcomes. Metabolite pathway analysis was also executed to identify potential metabolic pathways.ResultsAfter a series of validations and corrected for False discovery rate (FDR), we found a significant association between 1,5-anhydroglucitol (OR = 2.00, 95% CI: 1.39-2.89, P = 0.0002) and PH, and a significant association between pyridoxalate (OR = 0.59, 95% CI: 0.43-0.81, P = 0.0009) and 1-a achidonoylglycerophosphocholine (OR = 1.78, 95% CI: 1.22-2.58, P = 0.0026) had a suggested association with PH. In addition, the vitamin B6 metabolic pathway was also determined to be associated with PH.ConclusionConclusively, we isolated 1,5-anhydroglucitol, 1-arachidonoylglycerophosphocholine, and pyridoxate as causally implicated in PH, thereby proffering substantial theoretical substantiation for the formulation of future PH prevention and screening paradigms.
| S-EPMC11518716 | biostudies-literature
Project description:Background and aimsThe aim is to investigate the cause-and-effect connection between metabolites found in blood/urine and the likelihood of developing periodontal disease (PD) through the utilization of a two-sample Mendelian randomization (MR) method.MethodsUsing an inverse variance weighted (IVW) method and two additional two-sample MR models, we examined the relationship between blood/urine metabolites and PD by analyzing data from a comprehensive metabolome-based genome-wide association study and the Genome-Wide Association Studies (GWAS) of PD. To assess the consistency and dependability of the findings, diversity, cross-effects, and sensitivity analyses were conducted.ResultsOut of the 35 metabolites found in blood and urine, a total of eight metabolites (C-reactive protein, Potassium in urine, Urea, Cystatin C, Non-albumin protein, Creatinine, estimated Glomerular Filtration Rate, and Phosphate) displayed a possible causal connection with the risk of dental caries/PD using the inverse variance weighted (IVW) method (p < 0.05). This includes five metabolites in the blood and three in the urine. No metabolites were statistically significant in IVW MR models (p < 3.68 × 10- 4). Even after conducting sensitivity analysis with the leave-one-out method and removing the confounding instrumental variables, the impact of these factors on dental caries/PD remained significant.ConclusionBased on the available evidence, it is not possible to establish a significant causal link between the 35 blood metabolites and the likelihood of developing dental caries and PD.
| S-EPMC10925816 | biostudies-literature
Project description:We addressed fundamental questions about the influence of metabolites on the development of Diabetic retinopathy (DR), and explored the related pathological mechanism. Genome-wide association study (GWAS) database data for metabolites and DR were used to perform Mendelian randomization (MR) studies. The inverse variance weighting (IVW) was chosen as the primary analysis method. Sensitivity analysis was conducted using MR-PRESSO, leave-one-out and Cochran's Q test. Confounding factors were eliminated to ensure robustness. We also conducted metabolic pathway analysis. In vivo experimental validation was conducted using Sprague Dawley rats. The serum metabolites of the DR group rats and normal group rats were examined to evaluate the MR results. The screen identified eighteen metabolites associated with DR risk, twelve of which were known components. Seven metabolites were positively correlated with DR risk, while five could reduce it. Eight metabolites associated with proliferative DR (PDR) risk were identified, four of which are known components. Three of these were positively associated with PDR risk and one metabolite reduced PDR risk. Additionally, two possible metabolic pathways involved in the biological mechanism of DR were identified. The ELISA results showed that the serum levels of isoleucine and 4-HPA were significantly increased in DR rats, while the level of inosine was decreased. This study offers novel insights into the biological mechanisms underlying DR. Metabolites that are causally linked to DR may serve as promising biomarkers and therapeutic targets.
| S-EPMC11450153 | biostudies-literature
Project description:The lack of rapidly progressive murine models reflecting the classical infantile disease in ARPKD inhibits progress to understanding pathogenesis. The role that primary cilia play in PKD is also controversial. Here new mouse and rat models, generated by interbreeding appropriate ARPKD and ADPKD strains are characterized; better reflecting the severe human disease. Analysis of mRNA expression in the individual ARPKD and ADPKD models, and the combined mice highlighted different disrupted pathways but with a commonality of dysregulated mechanisms associated with primary cilia. These models will help understand ARPKD and improve preclinical testing for this disease. The study also, in unbiased way, reinforces that cilia are important for pathogenesis in both disorders.
2019-09-01 | GSE131277 | GEO