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59 result(s) for "Aldrich, Melinda C."
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Cross-talks between gut microbiota and tobacco smoking: a two-sample Mendelian randomization study
Background Considerable evidence has been reported that tobacco use could cause alterations in gut microbiota composition. The microbiota-gut–brain axis also in turn hinted at a possible contribution of the gut microbiota to smoking. However, population-level studies with a higher evidence level for causality are lacking. Methods This study utilized the summary-level data of respective genome-wide association study (GWAS) for 211 gut microbial taxa and five smoking phenotypes to reveal the causal association between the gut microbiota and tobacco smoking. Two-sample bidirectional Mendelian randomization (MR) design was deployed and comprehensively sensitive analyses were followed to validate the robustness of results. We further performed multivariable MR to evaluate the effect of neurotransmitter-associated metabolites on observed associations. Results Our univariable MR results confirmed the effects of smoking on three taxa ( Intestinimonas , Catenibacterium , and Ruminococcaceae , observed from previous studies) with boosted evidence level and identified another 13 taxa which may be causally affected by tobacco smoking. As for the other direction, we revealed that smoking behaviors could be potential consequence of specific taxa abundance. Combining with existing observational evidence, we provided novel insights regarding a positive feedback loop of smoking through Actinobacteria and indicated a potential mechanism for the link between parental smoking and early smoking initiation of their children driven by Bifidobacterium . The multivariable MR results suggested that neurotransmitter-associated metabolites (tryptophan and tyrosine, also supported by previous studies) probably played a role in the action pathway from the gut microbiota to smoking, especially for Actinobacteria and Peptococcus . Conclusions In summary, the current study suggested the role of the specific gut microbes on the risk for cigarette smoking (likely involving alterations in metabolites) and in turn smoking on specific gut microbes. Our findings highlighted the hazards of tobacco use for gut flora dysbiosis and shed light on the potential role of specific gut microbiota for smoking behaviors.
Sex modifies the effect of genetic risk scores for polycystic ovary syndrome on metabolic phenotypes
Females with polycystic ovary syndrome (PCOS), the most common endocrine disorder in women, have an increased risk of developing cardiometabolic disorders such as insulin resistance, obesity, and type 2 diabetes (T2D). While only diagnosable in females, males with a family history of PCOS can also exhibit a poor cardiometabolic profile. Therefore, we aimed to elucidate the role of sex in the cardiometabolic comorbidities observed in PCOS by conducting bidirectional genetic risk score analyses in both sexes. We first conducted a phenome-wide association study (PheWAS) using PCOS polygenic risk scores (PCOS PRS ) to identify potential pleiotropic effects of PCOS PRS across 1,380 medical conditions recorded in the Vanderbilt University Medical Center electronic health record (EHR) database, in females and males. After adjusting for age and genetic ancestry, we found that European (EUR)-ancestry males with higher PCOS PRS were significantly more likely to develop hypertensive diseases than females at the same level of genetic risk. We performed the same analysis in an African (AFR)-ancestry population, but observed no significant associations, likely due to poor trans-ancestry performance of the PRS. Based on observed significant associations in the EUR-ancestry population, we then tested whether the PRS for comorbid conditions (e.g., T2D, body mass index (BMI), hypertension, etc.) also increased the odds of a PCOS diagnosis. Only BMI PRS and T2D PRS were significantly associated with a PCOS diagnosis in EUR-ancestry females. We then further adjusted the T2D PRS for measured BMI and BMI residual (regressed on the BMI PRS and enriched for the environmental contribution to BMI). Results demonstrated that genetically regulated BMI primarily accounted for the relationship between T2D PRS and PCOS. Overall, our findings show that the genetic architecture of PCOS has distinct sex differences in associations with genetically correlated cardiometabolic traits. It is possible that the cardiometabolic comorbidities observed in PCOS are primarily explained by their shared genetic risk factors, which can be further influenced by biological variables including sex and BMI.
The Great Migration and African-American Genomic Diversity
We present a comprehensive assessment of genomic diversity in the African-American population by studying three genotyped cohorts comprising 3,726 African-Americans from across the United States that provide a representative description of the population across all US states and socioeconomic status. An estimated 82.1% of ancestors to African-Americans lived in Africa prior to the advent of transatlantic travel, 16.7% in Europe, and 1.2% in the Americas, with increased African ancestry in the southern United States compared to the North and West. Combining demographic models of ancestry and those of relatedness suggests that admixture occurred predominantly in the South prior to the Civil War and that ancestry-biased migration is responsible for regional differences in ancestry. We find that recent migrations also caused a strong increase in genetic relatedness among geographically distant African-Americans. Long-range relatedness among African-Americans and between African-Americans and European-Americans thus track north- and west-bound migration routes followed during the Great Migration of the twentieth century. By contrast, short-range relatedness patterns suggest comparable mobility of ∼15-16km per generation for African-Americans and European-Americans, as estimated using a novel analytical model of isolation-by-distance.
Genetically regulated eRNA expression predicts chromatin contact frequency and reveals genetic mechanisms at GWAS loci
The biological functions of extragenic enhancer RNAs and their impact on disease risk remain relatively underexplored. In this work, we develop in silico models of genetically regulated expression of enhancer RNAs across 49 cell and tissue types, characterizing their degree of genetic control. Leveraging the estimated genetically regulated expression for enhancer RNAs and canonical genes in a large-scale DNA biobank (N > 70,000) and high-resolution Hi-C contact data, we train a deep learning-based model of pairwise three-dimensional chromatin contact frequency for enhancer-enhancer and enhancer-gene pairs in cerebellum and whole blood. Notably, the use of genetically regulated expression of enhancer RNAs provides substantial tissue-specific predictive power, supporting a role for these transcripts in modulating spatial chromatin organization. We identify schizophrenia-associated enhancer RNAs independent of GWAS loci using enhancer RNA-based TWAS and determine the causal effects of these enhancer RNAs using Mendelian randomization. Using enhancer RNA-based TWAS, we generate a comprehensive resource of tissue-specific enhancer associations with complex traits in the UK Biobank. Finally, we show that a substantially greater proportion (63%) of GWAS associations colocalize with causal regulatory variation when enhancer RNAs are included. Here, the authors present trained models of genetically regulated enhancer RNA expression, finding that genetically regulated expression predicts chromatin contact frequency and that enhancer RNAs play a key role in complex trait heritability.
Cardiovascular Disease Risk Factors in Ghana during the Rural-to-Urban Transition: A Cross-Sectional Study
Populations in sub-Saharan Africa are shifting from rural to increasingly urban. Although the burden of cardiovascular disease is expected to increase with this changing landscape, few large studies have assessed a wide range of risk factors in urban and rural populations, particularly in West Africa. We conducted a cross-sectional, population-based survey of 3317 participants from Ghana (≥18 years old), of whom 2265 (57% female) were from a mid-sized city (Sunyani, population ~250,000) and 1052 (55% female) were from surrounding villages (populations <5000). We measured canonical cardiovascular disease risk factors (BMI, blood pressure, fasting glucose, lipids) and fibrinolytic markers (PAI-1 and t-PA), and assessed how their distributions and related clinical outcomes (including obesity, hypertension and diabetes) varied with urban residence and sex. Urban residence was strongly associated with obesity (OR: 7.8, 95% CI: 5.3-11.3), diabetes (OR 3.6, 95% CI: 2.3-5.7), and hypertension (OR 3.2, 95% CI: 2.6-4.0). Among the quantitative measures, most affected were total cholesterol (+0.81 standard deviations, 95% CI 0.73-0.88), LDL cholesterol (+0.89, 95% CI: 0.79-0.99), and t-PA (+0.56, 95% CI: 0.48-0.63). Triglycerides and HDL cholesterol profiles were similarly poor in both urban and rural environments, but significantly worse among rural participants after BMI-adjustment. For most of the risk factors, the strength of the association with urban residence did not vary with sex. Obesity was a major exception, with urban women at particularly high risk (26% age-standardized prevalence) compared to urban men (7%). Overall, urban residents had substantially worse cardiovascular risk profiles, with some risk factors at levels typically seen in the developed world.
Neighborhood-level deprivation and survival in lung cancer
Background Despite recent advances in lung cancer therapeutics and improving overall survival, disparities persist among socially disadvantaged populations. This study aims to determine the effects of neighborhood deprivation indices (NDI) on lung cancer mortality. This is a multicenter retrospective cohort study assessing the relationship between NDI and overall survival adjusted for age, disease stage, and DNA methylation among biopsy-proven lung cancer patients. State-specific NDI for each year of sample collection were computed at the U.S. census tract level and dichotomized into low- and high-deprivation. Results A total of 173 non small lung cancer patients were included, with n  = 85 (49%) and n  = 88 (51%) in the low and high-deprivation groups, respectively. NDI was significantly higher among Black patients when compared with White patients ( p  = 0.003). There was a significant correlation between DNA methylation and stage for HOXA7, SOX17, ZFP42, HOXA9, CDO1 and TAC1. Only HOXA7 DNA methylation was positively correlated with NDI. The high-deprivation group had a statistically significant shorter survival than the low-deprivation group ( p  = 0.02). After adjusting for age, race, stage, and DNA methylation status, belonging to the high-deprivation group was associated with higher mortality with a hazard ratio of 1.81 (95%CI: 1.03–3.19). Conclusions Increased neighborhood-level deprivation may be associated with liquid biopsy DNA methylation, shorter survival, and increased mortality. Changes in health care policies that consider neighborhood-level indices of socioeconomic deprivation may enable a more equitable increase in lung cancer survival.
Genetic variation in the eicosanoid pathway is associated with non-small-cell lung cancer (NSCLC) survival
Globally, lung cancer results in more deaths worldwide than any other cancer, indicating a need for better treatments. Members of the eicosanoid metabolism pathway represent promising therapeutic targets, as several enzymes involved in the generation of these lipids are dysregulated in many cancers and their inhibition reduces lung cancer growth in mouse models. However, genetic variation of enzymes involved in eicosanoid metabolism has not been adequately examined for association with lung cancer. The goal of this study was to determine whether germline genetic variation altering eicosanoid producing enzyme function and/or expression are associated with differences in lung cancer survival. We examined the association of genetic variation with mortality within eicosanoid metabolism genes in 395 non-small-cell lung cancer (NSCLC) cases from the Southern Community Cohort Study (SCCS). A total of 108 SNPs, both common and rare, in 19 genes, were examined for association. No common or rare variants were associated with lung cancer survival across the entire study population. However, rare variants in ALOX15B (arachidonate 15-lipoxygenase, type B) and the common variant rs12529 in AKR1C3 (prostaglandin F synthase) were associated with NSCLC mortality in women and African Americans, respectively. Rare variants in ALOX15B were associated with greater mortality in women (HR = 2.10, 95% CI = 1.25-3.54, p-value = 0.005). The major allele of rs12529 in AKCR1C3 associated with improved survival in African Americans (HR = 0.74, 95% CI = 0.59-0.92, p-value = 0.008). The lack of genetic associations among all NSCLC cases and the association among women only for rare variants in ALOX15B may, in part, explain the better NSCLC survival observed among women. These results raise the possibility that some subgroups within the NSCLC population may benefit from drugs targeting eicosanoid metabolism.
Germline prediction of immune checkpoint inhibitor discontinuation for immune-related adverse events
IntroductionImmune checkpoint inhibitors (ICIs) can yield remarkable clinical responses in subsets of patients with solid tumors, but they also commonly cause immune-related adverse events (irAEs). The predictive features of clinically severe irAEs leading to cessation of ICIs have yet to be established. Given the similarities between irAEs and autoimmune diseases, we sought to investigate the association of a germline polygenic risk score for autoimmune disease and discontinuation of ICIs due to irAEs.MethodsThe Genetics of immune-related adverse events and Response to Immunotherapy (GeRI) cohort comprises 1302 patients with non-small cell lung cancer (NSCLC) who received ICI therapy between 2009 and 2022 at four academic medical centers. We used a published polygenic risk score for autoimmune diseases (PRSAD) in the general population and validated it in the All of Us. We then assessed the association between PRSAD and cessation of ICI therapy due to irAEs in the GeRI cohort, using cause-specific and Fine-Gray subdistribution hazard models. To further understand the differential effects of type of therapy on the association between PRSAD and cessation of ICI due to irAEs, we conducted a stratified analysis by type of ICI therapy.ResultsUsing a competing risk model, we found an association between PRSAD and ICI cessation due to irAEs (HR per SD=1.24, p=0.004). This association was particularly strong in patients who had ICI cessation due to irAEs within 3 months of therapy initiation (HR per SD=1.40, p=0.005). Individuals in the top quintile of PRSAD had 4.8% ICI discontinuation for irAEs by 3 months, compared with 2% discontinuation by 3 months among patients in the bottom quintile (log-rank p=0.03). In addition, among patients who received combination programmed cell death protein-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte associated protein 4 (CTLA4) inhibitors, ICI discontinuation for irAEs by 3 months occurred in 4 of the 13 patients (30.8%) with high PRSAD genetic risk (top quintile) versus 3 of 21 patients (14.3%) with low PRSAD genetic risk (bottom quintile).ConclusionsWe demonstrate an association between a polygenic risk score for autoimmune disease and early ICI discontinuation for irAEs. Our results suggest that germline genetics may be used as an adjunctive tool for risk stratification around ICI clinical decision-making in solid tumor oncology.
Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action
A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.
Clinical insights into pulmonary hypertension in chronic obstructive pulmonary disease
Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD). Little is known about the prevalence and clinical profiles of patients with COPD‐PH. We report the clinical characteristics, hemodynamic profiles, and prognosis in a large population of patients with COPD referred for right heart catheterization (RHC). We extracted data from all patients referred for RHC between 1997 and 2017 in Vanderbilt's deidentified medical record. PH was defined as mean pulmonary artery pressure >20 mmHg. Pre‐ and postcapillary PH were defined according to contemporary guidelines. COPD was identified using a validated rules‐based algorithm requiring international classification of diseases codes relevant to COPD. We identified 6065 patients referred for RHC, of whom 1509 (24.9%) had COPD and 1213 had COPD and PH. Patients with COPD‐PH had a higher prevalence of diabetes, atrial fibrillation, and heart failure compared with COPD without PH. Approximately 55% of patients with COPD‐PH had elevated left ventricle (LV) filling pressure. Pulmonary function testing data from individuals with COPD‐PH revealed subtype differences, with precapillary COPD‐PH having lower diffusion capacity of the lungs for carbon monoxide (DLCO) values than the other COPD‐PH subtypes. Patients with COPD‐PH had significantly increased mortality compared with COPD alone (hazard ratio [HR]: 1.70, 95% confidence interval [CI]: 1.28–2.26) with the highest mortality among the combined pre‐ and postcapillary COPD‐PH subgroup (HR: 2.39; 95% CI: 1.64–3.47). PH is common among patients with COPD referred for RHC. The etiology of PH in patients with COPD is often mixed due to multimorbidity and is associated with high mortality, which may have implications for risk factor management.