Dataset Information

Sex-specific clustering of metabolic risk factors and cancer risk: a longitudinal study in Iran.

ABSTRACT: BACKGROUND:Cancer is a major cause of death in low- and middle-income countries. A large number of studies have shown that some of the metabolic risk factors (MRFs) tend to cluster in individuals. We examined the synergistic effects of multiple MRFs and cancer risk among Iranian adults. METHODS:Among 8593 (3929 men) participants aged ? 30 years, the self-organizing map (SOM) was applied to clustering of four MRFs including high fasting plasma glucose (HFPG), high total cholesterol (HTC), high systolic blood pressure (HSBP), and high body mass index (HBMI). The Cox proportional hazards model was used to investigate the association between clusters with cancer incidence during a median of 14.0 years of follow-up. RESULTS:During the study period, 265 new cases of cancer were identified among participants at risk. The incidence density rate was 2.5 per 1000 person years in total population. About 32 and 40% of men and women, respectively, had three or four MRFs. We identified seven clusters of MRFs in both men and women. In both genders, MRFs were clustered in those with older age. Further, inverse associations were found between current smoking in men, and education level and passive smoking in women and clustering of MRFs. In men, a cluster with 100% HSBP and HBMI had the highest risk for overall cancer. While, among women, a cluster with 100% HFPG and 93% HBMI yielded the highest risk for cancer. The risk was decreased when HBMI accompanied by HTC. CONCLUSIONS:Clustering patterns may reflect underlying link between MRFs and cancer and could potentially facilitate tailored health promotion interventions.

SUBMITTER: Ramezankhani A

PROVIDER: S-EPMC7183600 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Sex-specific clustering of metabolic risk factors and cancer risk: a longitudinal study in Iran.

Ramezankhani Azra A Azizi Fereidoun F Hadaegh Farzad F Hadaegh Farzad F

Biology of sex differences 20200425 1

<h4>Background</h4>Cancer is a major cause of death in low- and middle-income countries. A large number of studies have shown that some of the metabolic risk factors (MRFs) tend to cluster in individuals. We examined the synergistic effects of multiple MRFs and cancer risk among Iranian adults.<h4>Methods</h4>Among 8593 (3929 men) participants aged ≥ 30 years, the self-organizing map (SOM) was applied to clustering of four MRFs including high fasting plasma glucose (HFPG), high total cholesterol ...[more]

PMID: 32334634

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Project description:BackgroundTo identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population.Methods and findingsOne thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of Group 3 and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of Group 3 and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine.ConclusionsThe results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors.

Project description:Metabolic dysregulation underlies key metabolic risk factors—obesity, dyslipidemia, and dysglycemia.To uncover mechanistic links between metabolomic dysregulation and metabolic risk by testing metabolite associations with risk factors cross-sectionally and with risk factor changes over time.Cross-sectional—discovery samples (n = 650; age, 36–69 years) from the Framingham Heart Study (FHS) and replication samples (n = 670; age, 61–76 years) from the BioImage Study, both following a factorial design sampled from high vs low strata of body mass index, lipids, and glucose. Longitudinal—FHS participants (n = 554) with 5–7 years of follow-up for risk factor changes.Observational studies.Cross-sectional samples with or without obesity, dysglycemia, and dyslipidemia, excluding prevalent cardiovascular disease and diabetes or dyslipidemia treatment. Age- and sex-matched by group.None.Gas chromatography-mass spectrometry detected 119 plasma metabolites. Cross-sectional associations with obesity, dyslipidemia, and dysglycemia were tested in discovery, with external replication of 37 metabolites. Single- and multi-metabolite markers were tested for association with longitudinal changes in risk factors.Cross-sectional metabolite associations were identified with obesity (n = 26), dyslipidemia (n = 21), and dysglycemia (n = 11) in discovery. Glutamic acid, lactic acid, and sitosterol associated with all three risk factors in meta-analysis (P < 4.5 × 10?4). Metabolites associated with longitudinal risk factor changes were enriched for bioactive lipids. Multi-metabolite panels explained 2.5–15.3% of longitudinal changes in metabolic traits.Cross-sectional results implicated dysregulated glutamate cycling and amino acid metabolism in metabolic risk. Certain bioactive lipids were associated with risk factors cross-sectionally and over time, suggesting their upstream role in risk factor progression. Functional studies are needed to validate findings and facilitate translation into treatments or preventive measures.

Dataset Information

Sex-specific clustering of metabolic risk factors and cancer risk: a longitudinal study in Iran.

Publications

Sex-specific clustering of metabolic risk factors and cancer risk: a longitudinal study in Iran.

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