Integrative network analysis reveals different pathophysiological mechanisms of insulin resistance among Caucasians and African Americans

Multi-omic integration reveals cell-type-specific regulatory networks of insulin resistance in distinct ancestry populations

Our knowledge of the cell-type-specific mechanisms of insulin resistance remains limited. To dissect the cell-type-specific molecular signatures of insulin resistance, we performed a multiscale gene network analysis of adipose and muscle tissues in African and European ancestry populations. In adipose tissues, a comparative analysis revealed ethnically conserved cell-type signatures and two adipocyte subtype-enriched modules with opposite insulin sensitivity responses. The modules enriched for adipose stem and progenitor cells as well as immune cells showed negative correlations with insulin sensitivity. In muscle tissues, the modules enriched for stem cells and fibro-adipogenic progenitors responded to insulin sensitivity oppositely. The adipocyte and muscle fiber-enriched modules shared cellular-respiration-related genes but had tissue-specific rearrangements of gene regulations in response to insulin sensitivity. Integration of the gene co-expression and causal networks further pinpointed key drivers of insulin resistance. Together, this study revealed the cell-type-specific transcriptomic networks and signaling maps underlying insulin resistance in major glucose-responsive tissues. A record of this paper's transparent peer review process is included in the supplemental information.

Ethnic disparities attributed to the manifestation in and response to type 2 diabetes: insights from metabolomics

Type 2 diabetes (T2D) associated health disparities among different ethnicities have long been known. Ethnic variations also exist in T2D related comorbidities including insulin resistance, vascular complications and drug response. Genetic heterogeneity, dietary patterns, nutrient metabolism and gut microbiome composition attribute to ethnic disparities in both manifestation and progression of T2D. These factors differentially regulate the rate of metabolism and metabolic health. Metabolomics studies have indicated significant differences in carbohydrate, lipid and amino acid metabolism among ethnicities. Interestingly, genetic variations regulating lipid and amino acid metabolism might also contribute to inter-ethnic differences in T2D. Comprehensive and comparative metabolomics analysis between ethnicities might help to design personalized dietary regimen and newer therapeutic strategies. In the present review, we explore population based metabolomics data to identify inter-ethnic differences in metabolites and discuss how (a) genetic variations, (b) dietary patterns and (c) microbiome composition may attribute for such differences in T2D.

The Role of Gut Microbiota and Its Produced Metabolites in Obesity, Dyslipidemia, Adipocyte Dysfunction, and Its Interventions

Obesity is becoming an increasing problem worldwide and is often, but not invariably, associated with dyslipidemia. The gut microbiota is increasingly linked to cardiovascular disease, nonalcoholic fatty liver disease, and type 2 diabetes mellitus. However, relatively little focus has been attributed to the role of gut-microbiota-derived metabolites in the development of dyslipidemia and alterations in lipid metabolism. In this review, we discuss current data involved in these processes and point out the therapeutic potentials. We cover the ability of gut microbiota metabolites to alter lipoprotein lipase action, VLDL secretion, and plasma triglyceride levels, and its effects on reverse cholesterol transport, adipocyte dysfunction, and adipose tissue inflammation. Finally, the current intervention strategies for treatment of obesity and dyslipidemia is addressed with emphasis on the role of gut microbiota metabolites and its ability to predict treatment efficacies.

Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Background

Chronic lymphocytic leukemia (CLL) is an indolent heme malignancy characterized by the accumulation of CD5⁺ CD19⁺ B cells and episodes of relapse. The biological signaling that influence episodes of relapse in CLL are not fully described. Here, we identify gene networks associated with CLL relapse and survival risk.

Methods

Networks were investigated by using a novel weighted gene network co-expression analysis method and examining overrepresentation of upstream regulators and signaling pathways within co-expressed transcriptome modules across clinically annotated transcriptomes from CLL patients (N = 203). Gene Ontology analysis was used to identify biological functions overrepresented in each module. Differential Expression of modules and individual genes was assessed using an ANOVA (Binet Stage A and B relapsed patients) or T-test (SF3B1 mutations). The clinical relevance of biomarker candidates was evaluated using log-rank Kaplan Meier (survival and relapse interval) and ROC tests.

Results

Eight distinct modules (M2, M3, M4, M7, M9, M10, M11, M13) were significantly correlated with relapse and differentially expressed between relapsed and non-relapsed Binet Stage A CLL patients. The biological functions of modules positively correlated with relapse were carbohydrate and mRNA metabolism, whereas negatively correlated modules to relapse were protein translation associated. Additionally, M1, M3, M7, and M13 modules negatively correlated with overall survival. CLL biomarkers BTK, BCL2, and TP53 were co-expressed, while unmutated IGHV biomarker ZAP70 and cell survival-associated NOTCH1 were co-expressed in modules positively correlated with relapse and negatively correlated with survival days.

Conclusions

This study provides novel insights into CLL relapse biology and pathways associated with known and novel biomarkers for relapse and overall survival. The modules associated with relapse and overall survival represented both known and novel pathways associated with CLL pathogenesis and can be a resource for the CLL research community. The hub genes of these modules, e.g., ARHGAP27P2, C1S, CASC2, CLEC3B, CRY1, CXCR5, FUT5, MID1IP1, and URAHP, can be studied further as new therapeutic targets or clinical markers to predict CLL patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01012-y.

Differentially Expressed Genes and Enriched Signaling Pathways in the Adipose Tissue of Obese People

As the prevalence of obesity increases, so does the occurrence of obesity-related complications, such as cardiovascular and cerebrovascular diseases, diabetes, and some cancers. Increased adipose tissue is the main cause of harm in obesity. To better understand obesity and its related complications, we analyzed the mRNA expression profiles of adipose tissues from 126 patients with obesity and 275 non-obese controls. Using an integrated bioinformatics method, we explored the functions of 113 differentially expressed genes (DEGs) between them. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses revealed that upregulated DEGs were enriched in immune cell chemotaxis, complement-related cascade activation, and various inflammatory signaling pathways, while downregulated DEGs enriched in nutrient metabolism. The CIBERSORT algorithm indicated that an increase in macrophages may be the main cause of adipose tissue inflammation, while decreased γδ T cells reduce sympathetic action, leading to dysregulation of adipocyte thermogenesis. A protein-protein interaction network was constructed using the STRING database, and the top 10 hub genes were identified using the cytoHubba plug-in in Cytoscape. All were confirmed to be obesity-related using a separate dataset. In addition, we identified chemicals related to these hub genes that may contribute to obesity. In conclusion, we have successfully identified several hub genes in the development of obesity, which provide insights into the possible mechanisms controlling obesity and its related complications, as well as potential biomarkers and therapeutic targets for further research.

Integrative analyses of biomarkers and pathways for adipose tissue after bariatric surgery

We explored potential biomarkers and molecular mechanisms regarding multiple benefits after bariatric surgery. Differentially expressed genes (DEGs) for subcutaneous adipose tissue (AT) after bariatric surgery were identified by analyzing two expression profiles from the GEO. Subsequently, enrichment analysis, GSEA, PPI network, and gene-microRNAs and gene-TFs networks were interrogated to identify hub genes and associated pathways. Co-expressed DEGs included one that was up-regulated and 22 that were down-regulated genes. The enrichment analyses indicated that down-regulated DEGs were significantly involved in inflammatory responses. GSEA provided comprehensive evidence that most genes enriched in pro-inflammation pathways, while gene-sets after surgery enriched in metabolism. We identified nine hub genes in the PPI network, most of which were validated as highly expressed and hypomethylated in obesity by Attie Lab Diabetes and DiseaseMeth databases, respectively. DGIdb was also applied to predict potential therapeutic agents that might reverse abnormally high hub gene expression. Bariatric surgery induces a significant shift from an obese pro-inflammatory state to an anti-inflammatory state, with improvement in adipocyte metabolic function – representing key mechanisms whereby AT function improves after bariatric surgery. Our study deepens a mechanistic understanding of the benefits of bariatric surgery and provides potential biomarkers or treatment targets for further research.

Decreased Mitochondrial Dynamics Is Associated with Insulin Resistance, Metabolic Rate, and Fitness in African Americans

CONTEXT

African American women (AAW) have a higher incidence of insulin resistance and are at a greater risk for the development of obesity and type 2 diabetes than Caucasian women (CW). Although several factors have been proposed to mediate these racial disparities, the mechanisms remain poorly defined. We previously demonstrated that sedentary lean AAW have lower peripheral insulin sensitivity, reduced maximal aerobic fitness (VO2max), and lower resting metabolic rate (RMR) than CW. We have also demonstrated that skeletal muscle mitochondrial respiration is lower in AAW and appears to play a role in these racial differences.

OBJECTIVE

The goal of this study was to assess mitochondrial pathways and dynamics to examine the potential mechanisms of lower insulin sensitivity, RMR, VO2max, and mitochondrial capacity in AAW.

DESIGN

To achieve this goal, we assessed several mitochondrial pathways in skeletal muscle using gene array technology and semiquantitative protein analysis.

RESULTS

We report alterations in mitochondrial pathways associated with inner membrane small molecule transport genes, fusion-fission, and autophagy in lean AAW. These differences were associated with lower insulin sensitivity, RMR, and VO2max.

CONCLUSIONS

Together these data suggest that the metabolic racial disparity of insulin resistance, RMR, VO2max, and mitochondrial capacity may be mediated by perturbations in mitochondrial pathways associated with membrane transport, fission-fusion, and autophagy. The mechanisms contributing to these differences remain unknown.

A Comprehensive Survey of Immune Cytolytic Activity-Associated Gene Co-Expression Networks across 17 Tumor and Normal Tissue Types

Cytolytic immune activity in solid tissue can be quantified by transcript levels of two genes, GZMA and PRF1, which is named the CYT score. A previous study has investigated the molecular and genetic properties of tumors associated CYT, but a systematic exploration of how co-expression networks across different tumors are shaped by anti-tumor immunity is lacking. Here, we examined the connectivity and biological themes of CYT-associated modules in gene co-expression networks of 14 tumor and 3 matched normal tissues constructed from the RNA-Seq data of the "The Cancer Genome Atlas" project. We first found that tumors networks have more diverse CYT-correlated modules than normal networks. We next identified and investigated tissue-specific CYT-associated modules across 14 tumor types. Finally, a common CYT-associated network across 14 tumor types was constructed. Two common modules have mixed signs of correlation with CYT in different tumors. Given the tumors and normal tissues surveyed, our study presents a systematic view of the regulation of cytolytic immune activity across multiple tumor tissues.

Race-related differences in antibody responses to the inactivated influenza vaccine are linked to distinct pre-vaccination gene expression profiles in blood

We conducted a 5-year study analyzing antibody and B cell responses to the influenza A virus components of the inactivated influenza vaccine, trivalent (IIV3) or quadrivalent (IIV4) in younger (aged 35-45) and aged (≥65 years of age) Caucasian and African American individuals. Antibody titers to the two influenza A virus strains, distribution of circulating B cell subsets and the blood transcriptome were tested at baseline and after vaccination while expression of immunoregulatory markers on B cells were analyzed at baseline. African Americans mounted higher virus neutralizing and IgG antibody responses to the H1N1 component of IIV3 or 4 compared to Caucasians. African Americans had higher levels of circulating B cell subsets compared to Caucasians. Expression of two co-regulators, i.e., programmed death (PD)-1 and the B and T cell attenuator (BTLA) were differentially expressed in the two cohorts. Race-related differences were caused by samples from younger African Americans, while results obtained with samples of aged African Americans were similar to those of aged Caucasians. Gene expression profiling by Illumina arrays revealed highly significant differences in 1368 probes at baseline between Caucasians and African Americans although samples from both cohorts showed comparable changes in transcriptome following vaccination. Genes differently expressed between samples from African Americans and Caucasians regardless of age were enriched for myeloid genes, while the transcripts that differed in expression between younger African Americans and younger Caucasians were enriched for those specific for B-cells.

Changes of glucose levels precede dementia in African-Americans with diabetes but not in Caucasians

INTRODUCTION

Changes in glucose levels may represent a powerful metabolic indicator of dementia in African-Americans with diabetes. It is unclear whether these changes also occur in Caucasians.

METHODS

A secondary data analysis using electronic medical records from 5228 African-Americans and Caucasians aged ≥65 years was carried out. Mixed effects models with repeated serum glucose measurements were used to compare changes in glucose levels between African-Americans and Caucasian patients with and without incident dementia.

RESULTS

African-Americans and Caucasians with diabetes had significantly different changes in glucose levels by dementia status (P < .0001). African-Americans experienced a significant decline in glucose levels before the dementia diagnosis (estimated glucose decline 1.3421 mg/dL per year, P < .0001) than those who did not develop dementia. Caucasians with and without dementia showed stable glucose levels over time (P = .3071).

DISCUSSION

Significant changes in glucose levels precede dementia in African-American patients with diabetes but not in Caucasians.

The TMAO-Producing Enzyme Flavin-Containing Monooxygenase 3 Regulates Obesity and the Beiging of White Adipose Tissue

Emerging evidence suggests that microbes resident in the human intestine represent a key environmental factor contributing to obesity-associated disorders. Here, we demonstrate that the gut microbiota-initiated trimethylamine N-oxide (TMAO)-generating pathway is linked to obesity and energy metabolism. In multiple clinical cohorts, systemic levels of TMAO were observed to strongly associate with type 2 diabetes. In addition, circulating TMAO levels were associated with obesity traits in the different inbred strains represented in the Hybrid Mouse Diversity Panel. Further, antisense oligonucleotide-mediated knockdown or genetic deletion of the TMAO-producing enzyme flavin-containing monooxygenase 3 (FMO3) conferred protection against obesity in mice. Complimentary mouse and human studies indicate a negative regulatory role for FMO3 in the beiging of white adipose tissue. Collectively, our studies reveal a link between the TMAO-producing enzyme FMO3 and obesity and the beiging of white adipose tissue.

Dietary Quality and Ovarian Cancer Risk in African-American Women

This study evaluated 3 index-based dietary patterns-Healthy Eating Index (HEI)-2005, HEI-2010, and Alternate Healthy Eating Index (AHEI)-2010-in relation to ovarian cancer risk in African-American women. The study was conducted among 415 ovarian cancer cases and 629 age- and site-matched controls of African-American descent recruited from the population-based African American Cancer Epidemiology Study. Multivariable unconditional logistic regression models were used to estimate odds ratios and 95% confidence intervals between quartiles of dietary quality indices and ovarian cancer risk, adjusting for potential confounders. We found that higher AHEI-2010 scores, but not HEI-2005 or HEI-2010 scores, were associated with lower risk of ovarian cancer (comparing the highest quartile (4th) vs. lowest (1st), odds ratio (OR) = 0.66, 95% confidence interval (CI): 0.45, 0.98; P for trend = 0.05). When stratified by menopausal status, no noteworthy associations were observed among premenopausal women. However, among postmenopausal women, greater adherence to HEI-2010 (quartile 4 vs. quartile 1, OR = 0.57, 95% CI: 0.36, 0.92; P for trend = 0.03) and AHEI-2010 (quartile 4 vs. quartile 1, OR = 0.49, 95% CI: 0.31, 0.78; P for trend = 0.01) were inversely associated with ovarian cancer. Our findings indicate that adherence to an overall healthy dietary pattern may reduce ovarian cancer risk in African-American women, and particularly among postmenopausal African-American women.

Resolving multicopy duplications de novo using polyploid phasing

While the rise of single-molecule sequencing systems has enabled an unprecedented rise in the ability to assemble complex regions of the genome, long segmental duplications in the genome still remain a challenging frontier in assembly. Segmental duplications are at the same time both gene rich and prone to large structural rearrangements, making the resolution of their sequences important in medical and evolutionary studies. Duplicated sequences that are collapsed in mammalian de novo assemblies are rarely identical; after a sequence is duplicated, it begins to acquire paralog specific variants. In this paper, we study the problem of resolving the variations in multicopy long-segmental duplications by developing and utilizing algorithms for polyploid phasing. We develop two algorithms: the first one is targeted at maximizing the likelihood of observing the reads given the underlying haplotypes using discrete matrix completion. The second algorithm is based on correlation clustering and exploits an assumption, which is often satisfied in these duplications, that each paralog has a sizable number of paralog-specific variants. We develop a detailed simulation methodology, and demonstrate the superior performance of the proposed algorithms on an array of simulated datasets. We measure the likelihood score as well as reconstruction accuracy, i.e., what fraction of the reads are clustered correctly. In both the performance metrics, we find that our algorithms dominate existing algorithms on more than 93% of the datasets. While the discrete matrix completion performs better on likelihood score, the correlation clustering algorithm performs better on reconstruction accuracy due to the stronger regularization inherent in the algorithm. We also show that our correlation-clustering algorithm can reconstruct on an average 7.0 haplotypes in 10-copy duplication data-sets whereas existing algorithms reconstruct less than 1 copy on average.

DRUG-DRUG INTERACTION PROFILES OF MEDICATION REGIMENS EXTRACTED FROM A DE-IDENTIFIED ELECTRONIC MEDICAL RECORDS SYSTEM

With age, the number of prescribed medications increases and subsequently raises the risk for adverse drug-drug interactions. These adverse effects lower quality of life and increase health care costs. Quantifying the potential burden of adverse effects before prescribing medications can be a valuable contribution to health care. This study evaluated medication lists extracted from a subset of the Vanderbilt de-identified electronic medical record system. Reported drugs were cross-referenced with the Kyoto Encyclopedia of Genes and Genomes DRUG database to identify known drug-drug interactions. On average, a medication regimen contained 6.58 medications and 2.68 drug-drug interactions. Here, we quantify the burden of potential adverse events from drug-drug interactions through drug-drug interaction profiles and include a number of alternative medications as provided by the Anatomical Therapeutic Chemical Classification System.

Dietary carbohydrate intake, glycaemic load, glycaemic index and ovarian cancer risk in African-American women

Epidemiological evidence regarding the association between carbohydrate intake, glycaemic load (GL) and glycaemic index (GI) and risk of ovarian cancer has been mixed. Little is known about their impact on ovarian cancer risk in African-American women. Associations between carbohydrate quantity and quality and ovarian cancer risk were investigated among 406 cases and 609 controls using data from the African American Cancer Epidemiology Study (AACES). AACES is an ongoing population-based case-control study of ovarian cancer in African-Americans in the USA. Cases were identified through rapid case ascertainment and age- and site-matched controls were identified by random-digit dialling. Dietary information over the year preceding diagnosis or the reference date was obtained using a FFQ. Multivariable logistic regression models were used to estimate odds ratios and 95% CI adjusted for covariates. The OR comparing the highest quartile of total carbohydrate intake and total sugar intake v. the lowest quartile were 1·57 (95% CI 1·08, 2·28; P trend=0·03) and 1·61 (95% CI 1·12, 2·30; P trend<0·01), respectively. A suggestion of an inverse association was found for fibre intake. Higher GL was positively associated with the risk of ovarian cancer (OR 1·18 for each 10 units/4184 kJ (1000 kcal); 95% CI 1·04, 1·33). No associations were observed for starch or GI. Our findings suggest that high intake of total sugars and GL are associated with greater risk of ovarian cancer in African-American women.