Effects of glycemic traits on left ventricular structure and function: a mendelian randomization study

The effect of hyperlipidemia and body fat distribution on subclinical left ventricular function in obesity: a cardiovascular magnetic resonance study

BACKGROUND

Obesity is often associated with multiple comorbidities. However, whether obese subjects with hyperlipidemia in the absence of other complications have worse cardiac indices than metabolically healthy obese subjects is unclear. Therefore, we aimed to determine the effect of hyperlipidemia on subclinical left ventricular (LV) function in obesity and to evaluate the association of cardiac parameters with body fat distribution.

MATERIALS AND METHODS

Ninety-two adults were recruited and divided into 3 groups: obesity with hyperlipidemia (n = 24, 14 males), obesity without hyperlipidemia (n = 25, 13 males), and c ntrols (n = 43, 25 males). LV strain parameters (peak strain (PS), peak diastolic strain rate (PDSR), peak systolic strain rate) derived from cardiovascular magnetic resonance tissue tracking were measured and compared. Dual-energy X-ray absorptiometer was used to measure body fat distribution. Correlations of hyperlipidemia and body fat distribution with LV strain were assessed by multivariable linear regression.

RESULTS

Obese individuals with preserved LV ejection fraction showed lower global LV longitudinal, circumferential, and radial PS and longitudinal and circumferential PDSR than controls (all P < 0.05). Among obese patients, those with hyperlipidemia had lower longitudinal PS and PDSR and circumferential PDSR than those without hyperlipidemia (- 12.8 ± 2.9% vs. - 14.2 ± 2.7%, 0.8 ± 0.1 s-1 vs. 0.9 ± 0.3 s-1, 1.2 ± 0.2 s-1 vs. 1.4 ± 0.2 s-1; all P < 0.05). Multivariable linear regression demonstrated that hyperlipidemia was independently associated with circumferential PDSR (β = - 0.477, P < 0.05) in obesity after controlling for growth differences, other cardiovascular risk factors, and central fat distribution. In addition, android fat had an independently negative relationship with longitudinal and radial PS (β = - 0.486 and β = - 0.408, respectively; all P < 0.05); and visceral fat was negatively associated with longitudinal PDSR (β = - 0.563, P < 0.05). Differently, gynoid fat was positively correlated with circumferential PS and PDSR and radial PDSR (β = 0.490, β = 0.481, and β = 0.413, respectively; all P < 0.05).

CONCLUSION

Hyperlipidemia is independently associated with subclinical LV diastolic dysfunction in obesity. Central fat distribution (android and visceral fat) has a negative association, while peripheral fat distribution (gynoid fat) has a positive association on subclinical LV function. These results suggest that appropriate management of hyperlipidemia may be beneficial for obese patients, and that the differentiation of fat distribution in different regions may facilitate the precise management of obese patients. Clinical trials registration Effect of lifestyle intervention on metabolism of obese patients based on smart phone software (ChiCTR1900026476).

Effects of diabetes mellitus and glycemic traits on cardiovascular morpho-functional phenotypes

BACKGROUND

The effects of diabetes on the cardiac and aortic structure and function remain unclear. Detecting and intervening these variations early is crucial for the prevention and management of complications. Cardiovascular magnetic resonance imaging-derived traits are established endophenotypes and serve as precise, early-detection, noninvasive clinical risk biomarkers. We conducted a Mendelian randomization (MR) study to examine the association between two types of diabetes, four glycemic traits, and preclinical endophenotypes of cardiac and aortic structure and function.

METHODS

Independent genetic variants significantly associated with type 1 diabetes, type 2 diabetes, fasting insulin (FIns), fasting glucose (FGlu), 2 h-glucose post-challenge (2hGlu), and glycated hemoglobin (HbA1c) were selected as instrumental variables. The 96 cardiovascular magnetic resonance imaging traits came from six independent genome-wide association studies. These traits serve as preclinical endophenotypes and offer an early indication of the structure and function of the four cardiac chambers and two aortic sections. The primary analysis was performed using MR with the inverse-variance weighted method. Confirmation was achieved through Steiger filtering and testing to determine the causal direction. Sensitivity analyses were conducted using the weighted median, MR-Egger, and MR-PRESSO methods. Additionally, multivariable MR was used to adjust for potential effects associated with body mass index.

RESULTS

Genetic susceptibility to type 1 diabetes was associated with increased ascending aortic distensibility. Conversely, type 2 diabetes showed a correlation with a reduced diameter and areas of the ascending aorta, as well as decreased distensibility of the descending aorta. Genetically predicted higher levels of FGlu and HbA1c were correlated with a decrease in diameter and areas of the ascending aorta. Furthermore, higher 2hGlu levels predominantly showed association with a reduced diameter of both the ascending and descending aorta. Higher FIns levels corresponded to increased regional myocardial-wall thicknesses at end-diastole, global myocardial-wall thickness at end-diastole, and regional peak circumferential strain of the left ventricle.

CONCLUSIONS

This study provides evidence that diabetes and glycemic traits have a causal relationship with cardiac and aortic structural and functional remodeling, highlighting the importance of intensive glucose-lowering for primary prevention of cardiovascular diseases.

Effects of diabetes mellitus on left ventricular function and deformation in patients with restrictive cardiomyopathies: a 3.0T CMR feature tracking study

BACKGROUND

Diabetes mellitus (DM) is the most common metabolic disease worldwide and a major risk factor for adverse cardiovascular events, while the additive effects of DM on left ventricular (LV) deformation in the restrictive cardiomyopathy (RCM) cohort remain unclear. Accordingly, we aimed to investigate the additive effects of DM on LV deformation in patients with RCM.

MATERIALS AND METHODS

One hundred thirty-six RCM patients without DM [RCM(DM-)], 46 with DM [RCM (DM+)], and 66 age- and sex-matched control subjects who underwent cardiac magnetic resonance (CMR) scanning were included. LV function, late gadolinium enhancement (LGE) type, and LV global peak strains (including radial, circumferential, and longitudinal directions) were measured. The determinant of reduced LV global myocardial strain for all RCM patients was assessed using multivariable linear regression analyses. The receiver operating characteristic curve (ROC) was performed to illustrate the relationship between DM and decreased LV deformation.

RESULTS

Compared with the control group, RCM (DM-) and RCM(DM+) patients presented increased LV end-diastolic index and end-systolic volume index and decreased LV ejection fraction. LV GPS in all three directions and longitudinal PDSR progressively declined from the control group to the RCM(DM-) group to the RCM(DM+) group (all p < 0.05). DM was an independent determinant of impaired LV GPS in the radial, circumferential, and longitudinal directions and longitudinal PDSR (β =  - 0.217, 0.176, 0.253, and - 0.263, all p < 0.05) in RCM patients. The multiparameter combination, including DM, showed an AUC of 0.81(95% CI 0.75-0.87) to predict decreased LV GLPS and an AUC of 0.69 (95% CI 0.62-0.76) to predict decreased LV longitudinal PDSR.

CONCLUSIONS

DM may have an additive deleterious effect on LV dysfunction in patients with RCM, especially diastolic dysfunction in RCM patients, indicating the importance of early identification and initiation of treatment of DM in patients with RCM.

High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes

Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.

Associations of Insomnia With Insulin Resistance Traits: A Cross-sectional and Mendelian Randomization Study

CONTEXT

Insomnia is associated with insulin resistance (IR) in observational studies; however, whether insomnia is causally associated with IR remains unestablished.

OBJECTIVE

This study aims to estimate the causal associations of insomnia with IR and its related traits.

METHODS

In primary analyses, multivariable regression (MVR) and 1-sample Mendelian randomization (1SMR) analyses were performed to estimate the associations of insomnia with IR (triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol [TG/HDL-C] ratio) and its related traits (glucose level, TG, and HDL-C) in the UK Biobank. Thereafter, 2-sample MR (2SMR) analyses were used to validate the findings from primary analyses. Finally, the potential mediating effects of IR on the pathway of insomnia giving rise to type 2 diabetes (T2D) were examined using a 2-step MR design.

RESULTS

Across the MVR, 1SMR, and their sensitivity analyses, we found consistent evidence suggesting that more frequent insomnia symptoms were significantly associated with higher values of triglyceride-glucose index (MVR, β = 0.024, P < 2.00E-16; 1SMR, β = 0.343, P < 2.00E-16), TG/HDL-C ratio (MVR, β = 0.016, P = 1.75E-13; 1SMR, β = 0.445, P < 2.00E-16), and TG level (MVR, β = 0.019 log mg/dL, P < 2.00E-16, 1SMR: β = 0.289 log mg/dL, P < 2.00E-16) after Bonferroni adjustment. Similar evidence was obtained by using 2SMR, and mediation analysis suggested that about one-quarter (25.21%) of the association between insomnia symptoms and T2D was mediated by IR.

CONCLUSIONS

This study provides robust evidence supporting that more frequent insomnia symptoms are associated with IR and its related traits across different angles. These findings indicate that insomnia symptoms can be served as a promising target to improve IR and prevent subsequent T2D.

Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass

Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90th percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.