Gene and metabolite expression dependence on body mass index in human myocardium.
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ABSTRACT:
SUBMITTER: Adebayo AS
PROVIDER: S-EPMC8791972 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Body-mass index, abbreviated as BMI and given by M/H 2 with the mass M and the height H, has been widely used as a useful proxy to measure a general health status of a human individual. We generalise BMI in the form of M/H p and pursue to answer the question of the value of p for populations of animal species including human. We compare values of p for several different datasets for human populations with the ones obtained for other animal populations of fish, whales, and land mammals. All animal populations but humans analyzed in our work are shown to have p ≈ 3 unanimously. In contrast, human populations are different: As young infants grow to become toddlers and keep growing, the sudden change of p is observed at about one year after birth. Infants younger than one year old exhibit significantly larger value of p than two, while children between one and five years old show p ≈ 2, sharply different from other animal species. The observation implies the importance of the upright posture of human individuals. We also propose a simple mechanical model for a human body and suggest that standing and walking upright should put a clear division between bipedal human (p ≈ 2) and other animals (p ≈ 3).
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Project description:BackgroundA high body mass index (BMI) is a major risk factor for several chronic diseases, but the biology underlying these associations is not well-understood. Dyslipidemia, inflammation, and elevated levels of growth factors and sex steroid hormones explain some of the increased disease risk, but other metabolic factors not yet identified may also play a role.DesignIn order to discover novel metabolic biomarkers of BMI, we used non-targeted metabolomics to assay 317 metabolites in blood samples from 947 participants and examined the cross-sectional associations between metabolite levels and BMI. Participants were from three studies in the United States and China. Height, weight, and potential confounders were ascertained by questionnaire (US studies) or direct measurement (Chinese study). Metabolite levels were measured using liquid-phase chromatography and gas chromatography coupled with mass spectrometry. We evaluated study-specific associations using linear regression, adjusted for age, gender, and smoking, and we estimated combined associations using random effects meta-analysis.ResultsThe meta-analysis revealed 37 metabolites significantly associated with BMI, including 19 lipids, 12 amino acids, and 6 others, at the Bonferroni significance threshold (p<0.00016). Eighteen of these associations had not been previously reported, including histidine, an amino acid neurotransmitter, and butyrylcarnitine, a lipid marker of whole-body fatty acid oxidation. Heterogeneity by study was minimal (all Pheterogeneity >0.05). In total, 110 metabolites were associated with BMI at the p<0.05 level.ConclusionThese findings establish a baseline for the BMI metabolome, and suggest new targets for researchers attempting to clarify mechanistic links between high BMIs and disease risk.
| S-EPMC4169991 | biostudies-literature
Project description:Both genetic and environmental factors are suggested to influence overweight and obesity risks. Although individual loci and genes have been frequently shown to be associated with body mass index (BMI), the overall interaction of these genes and their role in BMI remains underexplored. Data were collected in 90 healthy, predominately Caucasian participants (51% female) with a mean age of 26.00 ± 9.02 years. Whole blood samples were assayed by Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. We integrated and analyzed the clinical and microarray gene expression data from those individuals to understand various systematic gene expression patterns underlying BMI. Conventional differential expression analysis identified seven genes RBM20, SEPT12, AX748233, SLC30A3, WTIP, CASP10, and OR12D3 associated with BMI. Weight gene co-expression network analysis among 4,647 expressed genes identified two gene modules associated with BMI. These two modules, with different extents of gene connectivity, are enriched for catabolic and muscle system processes respectively, and tend to be regulated by zinc finger transcription factors. A total of 246 hub genes were converted to non-hub genes, and 286 non-hub genes were converted to hub genes between normal and overweight individuals, revealing the network dynamics underlying BMI. A total of 28 three-way gene interactions were identified, suggesting the existence of high-order gene expression patterns underlying BMI. Our study demonstrated a variety of systematic gene expression patterns associated with BMI and thus provided novel understanding regarding the genetic factors for overweight and obesity risks on system levels.
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Project description:BackgroundRisk of substance dependence (SD) and obesity has been linked to the function of melanocortin peptides encoded by the proopiomelanocortin gene (POMC).Methods and resultsPOMC exons were Sanger sequenced in 280 African Americans (AAs) and 308 European Americans (EAs). Among them, 311 (167 AAs and 114 EAs) were affected with substance (alcohol, cocaine, opioid and/or marijuana) dependence and 277 (113 AAs and164 EAs) were screened controls. We identified 23 variants, including two common polymorphisms (rs10654394 and rs1042571) and 21 rare variants; 12 of which were novel. We used logistic regression to analyze the association between the two common variants and SD or body mass index (BMI), with sex, age, and ancestry proportion as covariates. The common variant rs1042571 in the 3'UTR was significantly associated with BMI in EAs (Overweight: P(adj) = 0.005; Obese: P(adj) = 0.018; Overweight+Obese: P(adj) = 0.002) but not in AAs. The common variant, rs10654394, was not associated with BMI and neither common variant was associated with SD in either population. To evaluate the association between the rare variants and SD or BMI, we collapsed rare variants and tested their prevalence using Fisher's exact test. In AAs, rare variants were nominally associated with SD overall and with specific SD traits (SD: P(FET,1df) = 0.026; alcohol dependence: P(FET,1df) = 0.027; cocaine dependence: P(FET,1df) = 0.007; marijuana dependence: P(FET,1df) = 0.050) (the P-value from cocaine dependence analysis survived Bonferroni correction). There was no such effect in EAs. Although the frequency of the rare variants did not differ significantly between the normal-weight group and the overweight or obese group in either population, certain rare exonic variants occurred only in overweight or obese subjects without SD.ConclusionThese findings suggest that POMC exonic variants may influence risk for both SD and elevated BMI, in a population-specific manner. However, common and rare variants in this gene may exert different effects on these two phenotypes.
| S-EPMC3444488 | biostudies-literature
Project description:Outcomes related to disordered metabolism are common in alcohol dependence (AD). To investigate alterations in the regulation of body mass that occur in the context of AD, we performed a genome-wide association study (GWAS) of body mass index (BMI) in African Americans (AAs) and European Americans (EAs) with AD. Subjects were recruited for genetic studies of AD or drug dependence and evaluated using the Semi-structured Assessment for Drug Dependence and Alcoholism. We investigated a total of 2587 AAs and 2959 EAs with DSM-IV AD diagnosis. In the stage 1 sample (N = 4137), we observed three genome-wide significant (GWS) single-nucleotide polymorphism associations, rs200889048 (P = 8.98 * 10-12 ) and rs12490016 (P = 1.44 * 10-8 ) in EAs and rs1630623 (P = 5.14 * 10-9 ) in AAs and EAs meta-analyzed. In the stage 2 sample (N = 1409), we replicated 278, 253 and 168 of the stage 1 suggestive loci (P < 5*10-4 ) in AAs, EAs, and AAs and EAs meta-analyzed, respectively. A meta-analysis of stage 1 and stage 2 samples (N = 5546) identified two additional GWS signals: rs28562191 in EAs (P = 4.46 * 10-8 ) and rs56950471 in AAs (P = 1.57 * 10-9 ). Three of the GWS loci identified (rs200889048, rs12490016 and rs1630623) were not previously reported by GWAS of BMI in the general population, and two of them raise interesting hypotheses: rs12490016-a regulatory variant located within LINC00880, where there are other GWAS-identified variants associated with birth size, adiposity in newborns and bulimia symptoms, which also interact with social stress in relation to birth size; rs1630623-a regulatory variant related to ALDH1A1, a gene involved in alcohol metabolism and adipocyte plasticity. These loci offer molecular insights regarding the regulatory mechanisms of body mass in the context of AD.
| S-EPMC5102811 | biostudies-literature
Project description:Seasonal influenza is a primary public health burden in the USA and globally. Annual vaccination programs are designed on the basis of circulating influenza viral strains. However, the effectiveness of the seasonal influenza vaccine is highly variable between seasons and among individuals. A number of factors are known to influence vaccination effectiveness including age, sex, and comorbidities. Here, we sought to determine whether whole blood gene expression profiling prior to vaccination is informative about pre-existing immunological status and the immunological response to vaccine. We performed whole transcriptome analysis using RNA sequencing (RNAseq) of whole blood samples obtained prior to vaccination from 275 participants enrolled in an annual influenza vaccine trial. Serological status prior to vaccination and 28 days following vaccination was assessed using the hemagglutination inhibition assay (HAI) to define baseline immune status and the response to vaccination. We find evidence that genes with immunological functions are increased in expression in individuals with higher pre-existing immunity and in those individuals who mount a greater response to vaccination. Using a random forest model, we find that this set of genes can be used to predict vaccine response with a performance similar to a model that incorporates physiological and prior vaccination status alone. A model using both gene expression and physiological factors has the greatest predictive power demonstrating the potential utility of molecular profiling for enhancing prediction of vaccine response. Moreover, expression of genes that are associated with enhanced vaccination response may point to additional biological pathways that contribute to mounting a robust immunological response to the seasonal influenza vaccine.
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Project description:Aging human males display reduced reproductive health, however testis aging is poorly understood at the molecular and genomic level. Here, we utilized single-cell RNA-seq to profile over 44,000 cells from both young and older men (>60 years old) – and examined age-related changes in germline development and in the somatic niche. Interestingly, age-related changes in spermatogonial stem cells appeared modest, whereas age-related dysregulation of spermatogenesis and the somatic niche ranged from moderate to severe. Altered pathways included signaling and inflammation in multiple cell types, metabolic signaling in Sertoli cells, hedgehog signaling and testosterone production in Leydig cells, cell death and growth in testicular peritubular cells, and possible developmental regression in both Leydig and peritubular cells. Remarkably, the extent of dysregulation correlated with body mass index in older, but not younger men. Taken together, we reveal candidate molecular mechanisms underlying the complex testicular changes conferred by aging, and their exacerbation by concurrent chronic conditions such as obesity.
2022-05-05 | GSE182786 | GEO
Project description:Higher body mass index (BMI) increases the risk of meniscus injury and knee osteoarthritis (OA). However, it is unknown if and how obesity affects meniscus biology. We analyzed transcriptome-wide gene expression profiles of injured human menisci to test the hypothesis that meniscal gene expression signatures relate to patient BMI.Meniscus samples were obtained from patients undergoing arthroscopic partial meniscectomy. Transcriptome-wide analysis of gene expression followed by validation of selected transcripts by QuantiGene Plex assay was performed. Correlations of gene expression with BMI and relative fold changes (?1.5-fold) in 3 BMI categories (lean [BMI 18.5-24.9 kg/m(2) ], overweight [BMI 25.0-29.9 kg/m(2) ], and obese [BMI >30.0 kg/m(2) ]) were analyzed, and integrated functional classifications were probed computationally.The obese versus overweight comparison resulted in the largest set of differences (565 transcripts) followed by obese versus lean (280 transcripts) and overweight versus lean (125 transcripts). Biologic reproducibility was confirmed by cluster analysis of expressed transcripts. Differentially regulated transcripts represented important functional classifications. Transcripts associated with oxygen transport, calcium ion binding, and cell homeostasis were elevated with BMI, while those related to extracellular matrix deposition, cell migration, and glucosamine metabolic processes were repressed. While these functional classifications may play key roles in cartilage/meniscus homeostasis, failure of extracellular matrix deposition and increase in calcium ion binding likely contribute to OA development following meniscal injury.Our results indicate greater differences in gene expression between obese and overweight groups than between overweight and lean groups. This may indicate that there is a weight threshold at which injured meniscus responds severely to increased BMI. BMI-related changes in gene expression present a plausible explanation for the role of meniscal injury in OA development among obese patients.
| S-EPMC4116431 | biostudies-literature
Project description:Here we derive candidate gene-environment interaction (GxE) variants from promoter-enhancer interacting regions that respond to dietary fatty acid challenge through altered chromatin accessibility in human primary adipocytes, and demonstrate that molecular genomics data produced in physiologically relevant contexts can illuminate new functional GxE mechanisms in humans and identify variants for GxE testing in large biobanks.
2019-06-17 | GSE129574 | GEO
Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.
| S-EPMC5710345 | biostudies-literature