Traditional Clinical Risk Factors Research Articles

A metabolomic index based on lipoprotein subfractions and branched chain amino acids is associated with incident hypertension

ObjectiveThe present study aims to evaluate the performance of the Diabetes Risk Index (DRI), a metabolomic index based on lipoprotein particles and branched chain amino acids, on the incidence of newly developed hypertension in a large community dwelling cohort. MethodsThe DRI was calculated by combining 6 lipoprotein parameters [sizes of very-low-density lipoprotein (VLDL), low-density lipoprotein (LDL) and high-density lipoprotein (HDL), concentrations of large VLDL, small LDL, and large HDL particles], and the concentrations of valine and leucine. DRI scores were estimated in 4169 participants from the PREVEND prospective cohort. Cox proportional hazards regression was used to evaluate the association of DRI scores with incident hypertension. ResultsDuring a median follow-up of 8.6 years, 924 new hypertension cases were ascertained. In analyses adjusted for age and sex, there was a significant association between DRI and incident hypertension with a hazard ratio (HR) per 1 SD increase of 1.45 (95% CI 1.36,1.54; p < 0.001). After additional adjustment for traditional risk factors, the HR remained significant (HRadj 1.21, 95% CI 1.10, 1.33, p <0.001). Likewise, subjects in the top quartile of DRI presented with a higher risk of hypertension (HRadj 1.64, 95% CI 1.28, 2.10, p <0.001). Furthermore, the net reclassification improvement assessment improved after the addition of DRI to a traditional risk model (p <0.001), allowing proper reclassification of 34% of the participants. ConclusionHigher DRI scores were associated with an increased risk of incident hypertension. Such association was independent of traditional clinical risk factors for hypertension.

Galectin-3 in Heart Failure with Preserved Ejection Fraction and Persistent Atrial Fibrillation Versus Sinus Rhythm. Correlation with Left Atrial Volume and N-Terminal Pro B-Type Natriuretic Peptide

Background: Galectin-3 (Gal-3) is considered both a profibrotic biomarker in Heart Failure with preserved Ejection Fraction (HFpEF) and a biomarker of atrial remodeling in Atrial Fibrillation (AF). The Left Atrial Volume Index (LAVI) is an echocardiographic parameter considered an index of left atrial remodeling. Aim of this study was to analyse the relation of Gal-3 levels with both LAVI and N-Terminal Pro B-Type Natriuretic Peptide (NT-proBNP) in patients with HFpEF and Persistent AF (HFpEF-PAF). Methods: Serum Gal-3 and NT-proBNP, along with LAVI were measured. A comparison of such parameters between 49 patients with HFpEF-PAF and 53 patients with HFpEF and sinus rhythm (HEpEF-SR) was made. Results: Galectin-3, NT-proBNP and LAVI were significantly higher in patients with HFpEF-PAF compared to HFpEF-SR (23±7 ng/mL vs 19.5±8.5 ng/mL, p=0.027; 3,406.8±2,321.9 pg/mL vs 1,459.6±1,372 pg/mL, p&lt;0.001; 40.1±11mL/m² vs 28.4±7.7 mL/m², p&lt;0.001, respectively). In HFpEF-PAF, Gal- 3 showed a significant correlation with both NT-proBNP (r=0.40, p=0.0038) and LAVI (r=0.28, p=0.044). We found a significant association between patients with higher levels of Gal-3 &gt;17.8 ng/mL and HFpEF-PAF (p=0.002). Finally, a multivariate logistic regression analysis adjusted for age, sex and traditional clinical AF risk factors showed that Gal-3 &gt;17,8 ng/mL (OR 3.862, 95% CI 1.416 to 10.532, p=0.008) was an independent predictor of PAF. Conclusions: In patients with HFpEF-PAF Gal-3 was higher and related with both NT-proBNP and LAVI. The latter correlation may be relevant because LAVI is considered an index of left atrial remodeling. Moreover, higher levels of Gal-3&gt;17,8 ng/mL were an independent predictor of PAF.

Characterizing Hypertensive Disorders of Pregnancy Among Medicaid Recipients in a Nonexpansion State.

Background: The incidence of hypertensive disorders of pregnancy (HDP) are on the rise in the United States, especially in the South, which has a heavy chronic disease burden and large number of Medicaid nonexpansion states. Sizeable disparities in HDP outcomes exist by race/ethnicity, geography, and health insurance coverage. Our objective is to explore HDP in the Alabama Medicaid maternity population, and the association of maternal sociodemographic, clinical, and care utilization characteristics with HDP diagnosis. Materials and Methods: Data were from Alabama Medicaid delivery claims in 2017. Bivariate analyses were used to examine maternal characteristics by HDP diagnosis. Hierarchical generalized linear models, with observations nested at the county level, were used to assess multivariable relationships between maternal characteristics and HDP diagnosis. Results: Among women with HDP diagnosis, a higher proportion were older, Black, had other comorbidities, and had more perinatal hospitalizations or emergency visits compared with those without HDP diagnosis. There were increased odds of an HDP diagnosis for older women and those with comorbidities. Black women (adjusted odds ratio [aOR] = 1.24, 95% confidence interval [CI]: 1.16-1.33), women insured only during pregnancy by Sixth Omnibus Reconciliation Act Medicaid (aOR = 1.08, 95% CI: 1.02-1.15), and women entering prenatal care (PNC) in the second trimester (aOR = 1.10, 95% CI: 1.03-1.18) had elevated odds of HDP diagnosis compared with their counterparts. Conclusions: Beyond traditional demographic and clinical risk factors, not having preconception insurance coverage or first trimester PNC entry were associated with higher odds of HDP diagnosis. Improving the provision and timing of maternity coverage among Medicaid recipients, particularly in nonexpansion states, may help identify and treat women at risk of HDP and associated adverse perinatal outcomes.

Abstract MP13: Lipid Peroxidation And Inflammatory Response Differentiate With Changes In Liver Fat Among Obese Latino Youth Following Lifestyle Intervention

Introduction: Lipid peroxidation and inflammation are pivotal pathological processes involved in the progression of NAFLD, a prelude to cardiovascular disease. Lifestyle intervention is the cornerstone approach for preventing cardiometabolic disease among high-risk populations, yet studies have not examined the mechanisms by which lifestyle intervention may mediate changes in liver fat in youth. Hypothesis: Lifestyle intervention will decrease hepatic fat fraction (HFF), tumor necrosis alpha (TNF)-α, and malondialdehyde (MDA)-protein adducts. Methods: Latino youth with obesity (n=26, age 13.9±1.3, BMI% 98.1±1.1) and prediabetes completed a 6-month lifestyle intervention that included nutrition education (1 d/wk) and physical activity (3 d/wk). HFF was measured by MRI before and after intervention. Fasting serum samples were collected for measurement of lipid peroxidation, measured by MDA-protein adducts, and inflammation, measured by TNF-α. Repeated measures ANOVA models were used to examine the effect of lifestyle intervention on HFF, MDA-protein adducts, and TNF-α. Data are presented as Mean±SE. Results: The intervention led to significant decreases in HFF (from 7.0±1.1% to 5.4±0.7%, p=0.027) and TNF-α (from 1.7±1.0 to 1.5±0.1 pg/mL, p=0.050), but not MDA-protein adducts (from 266.4±28.4 to 253.8±29.3 pmol/mL, p=0.105). However, there was significant heterogeneity in changes in HFF whereby those with the greatest response (n=14) decreased HFF by -44.0% while non-responders (n=12) increased HFF by 67.5%. HFF responders exhibited significantly greater reductions in MDA-protein adducts (from 256.2±39.4 to 228.1±40.0 pmol/mL, Δ-10.1%) compared to HFF non-responders (from 278.4±42.5 to 283.7±43.2 pmol/mL, Δ2.0%; p=0.023). TNF-α was reduced in HFF responders (from 1.8±0.2 to 1.5±0.1 pg/mL, Δ-17.8%) compared to HFF non-responders (from 1.5±0.2 to 1.5±0.1 pg/mL, Δ-4.4%) but was not significant (p=0.231). Conclusions: Reductions in HFF through lifestyle changes were associated with greater reductions in markers of lipid peroxidation, but not inflammation. The effect of lifestyle intervention on HFF may be mediated by markers that extend beyond traditional clinical risk factors among high-risk youth.

SelectMDx and Multiparametric Magnetic Resonance Imaging of the Prostate for Men Undergoing Primary Prostate Biopsy: A Prospective Assessment in a Multi-Institutional Study.

Simple SummaryProstate-specific antigen and digital rectal examination, used to guide prostate biopsy, often result in overdiagnosis of indolent prostate cancer (PCa) while missing clinically significant PCa (csPCa). The aim of this study was to evaluate the diagnostic accuracy of SelectMDx and its association with multiparametric magnetic resonance imaging (mpMRI) in predicting PCa in prostate biopsies. SelectMDx was revealed to be a good predictor of PCa, while with regards to csPCa detection, it was demonstrated to be less effective, showing results similar to mpMRI. The best diagnostic strategy to avoid unnecessary biopsy is performing SelectMDx after an initial negative mpMRI. Biopsy could be proposed for all cases of positive mpMRI and to those with a negative mpMRI followed by a positive SelectMDx.Prostate-specific antigen (PSA) testing as the sole indication for prostate biopsy lacks specificity, resulting in overdiagnosis of indolent prostate cancer (PCa) and missing clinically significant PCa (csPCa). SelectMDx is a biomarker-based risk score to assess urinary HOXC6 and DLX1 mRNA expression combined with traditional clinical risk factors. The aim of this prospective multi-institutional study was to evaluate the diagnostic accuracy of SelectMDx and its association with multiparametric magnetic resonance (mpMRI) when predicting PCa in prostate biopsies. Overall, 310 consecutive subjects were included. All patients underwent mpMRI and SelectMDx prior to prostate biopsy. SelectMDx and mpMRI showed sensitivity and specificity of 86.5% vs. 51.9%, and 73.8% vs. 88.3%, respectively, in predicting PCa at biopsy, and 87.1% vs. 61.3%, and 63.7% vs. 83.9%, respectively, in predicting csPCa at biopsy. SelectMDx was revealed to be a good predictor of PCa, while with regards to csPCa detection, it was demonstrated to be less effective, showing results similar to mpMRI. With analysis of strategies assessed to define the best diagnostic strategy to avoid unnecessary biopsy, SelectMDx appeared to be a reliable pathway after an initial negative mpMRI. Thus, biopsy could be proposed for all cases of mpMRI PI-RADS 4–5 score, and to those with Prostate Imaging-Reporting and Data System (PI-RADS) 1–3 score followed by a positive SelectMDx.

How Do We Incorporate Polygenic Risk Scores in Cardiovascular Disease Risk Assessment and Management?

The potential of polygenic risk scores (PRS) to improve atherosclerotic cardiovascular disease (ASCVD) risk assessment and management has stoked significant interest in their incorporation into clinical management. The goal of this review is to apprise the readers of the latest developments and evidence of PRS readiness for clinical integration. We also discuss current limitations that must be addressed before PRS can be implemented into routine clinical practice. PRS have been shown to improve risk stratification for ASCVD and to identify patients who may derive increased benefit from primary and secondary prevention. Risk captured by PRS appears largely independent of traditional risk factors and can be ascertained at birth, prior to the development of traditional clinical risk factors. Genetic risk is modifiable through lifestyle modifications and medications. PRS offers a valuable way to improve early identification of actionable CVD risk. However, further work is needed before PRS can be implemented clinically.

Using Ultrasound and Inflammation to Improve Prediction of Ischemic Stroke: A Secondary Analysis of the Multi-Ethnic Study of Atherosclerosis

Introduction: Current ischemic stroke risk prediction is primarily based on clinical factors, rather than imaging or laboratory markers. We examined the relationship between baseline ultrasound and inflammation measurements and subsequent primary ischemic stroke risk. Methods: In this secondary analysis of the Multi-Ethnic Study of Atherosclerosis (MESA), the primary outcome is the incident ischemic stroke during follow-up. The predictor variables are 9 carotid ultrasound-derived measurements and 6 serum inflammation measurements from the baseline study visit. We fit Cox regression models to the outcome of ischemic stroke. The baseline model included patient age, hypertension, diabetes, total cholesterol, smoking, and systolic blood pressure. Goodness-of-fit statistics were assessed to compare the baseline model to a model with ultrasound and inflammation predictor variables that remained significant when added to the baseline model. Results: We included 5,918 participants. The primary outcome of ischemic stroke was seen in 105 patients with a mean follow-up time of 7.7 years. In the Cox models, we found that carotid distensibility (CD), carotid stenosis (CS), and serum interleukin-6 (IL-6) were associated with incident stroke. Adding tertiles of CD, IL-6, and categories of CS to a baseline model that included traditional clinical vascular risk factors resulted in a better model fit than traditional risk factors alone as indicated by goodness-of-fit statistics. Conclusions: In a multiethnic cohort of patients without cerebrovascular disease at baseline, we found that CD, CS, and IL-6 helped predict the occurrence of primary ischemic stroke. Future research could evaluate if these basic ultrasound and serum measurements have implications for primary prevention efforts or clinical trial inclusion criteria.

Comparisons of Polyexposure, Polygenic, and Clinical Risk Scores in Risk Prediction of Type 2 Diabetes.

OBJECTIVETo establish a polyexposure score (PXS) for type 2 diabetes (T2D) incorporating 12 nongenetic exposures and examine whether a PXS and/or a polygenic risk score (PGS) improves diabetes prediction beyond traditional clinical risk factors.RESEARCH DESIGN AND METHODSWe identified 356,621 unrelated individuals from the UK Biobank of White British ancestry with no prior diagnosis of T2D and normal HbA1c levels. Using self-reported and hospital admission information, we deployed a machine learning procedure to select the most predictive and robust factors out of 111 nongenetically ascertained exposure and lifestyle variables for the PXS in prospective T2D. We computed the clinical risk score (CRS) and PGS by taking a weighted sum of eight established clinical risk factors and >6 million single nucleotide polymorphisms, respectively.RESULTSIn the study population, 7,513 had incident T2D. The C-statistics for the PGS, PXS, and CRS models were 0.709, 0.762, and 0.839, respectively. Individuals in the top 10% of PGS, PXS, and CRS had 2.00-, 5.90-, and 9.97-fold greater risk, respectively, compared to the remaining population. Addition of PGS and PXS to CRS improved T2D classification accuracy, with a continuous net reclassification index of 15.2% and 30.1% for cases, respectively, and 7.3% and 16.9% for controls, respectively.CONCLUSIONSFor T2D, the PXS provides modest incremental predictive value over established clinical risk factors. However, the concept of PXS merits further consideration in T2D risk stratification and is likely to be useful in other chronic disease risk prediction models.

Improved prediction of fracture risk leveraging a genome-wide polygenic risk score

BackgroundAccurately quantifying the risk of osteoporotic fracture is important for directing appropriate clinical interventions. While skeletal measures such as heel quantitative speed of sound (SOS) and dual-energy X-ray absorptiometry bone mineral density are able to predict the risk of osteoporotic fracture, the utility of such measurements is subject to the availability of equipment and human resources. Using data from 341,449 individuals of white British ancestry, we previously developed a genome-wide polygenic risk score (PRS), called gSOS, that captured 25.0% of the total variance in SOS. Here, we test whether gSOS can improve fracture risk prediction.MethodsWe examined the predictive power of gSOS in five genome-wide genotyped cohorts, including 90,172 individuals of European ancestry and 25,034 individuals of Asian ancestry. We calculated gSOS for each individual and tested for the association between gSOS and incident major osteoporotic fracture and hip fracture. We tested whether adding gSOS to the risk prediction models had added value over models using other commonly used clinical risk factors.ResultsA standard deviation decrease in gSOS was associated with an increased odds of incident major osteoporotic fracture in populations of European ancestry, with odds ratios ranging from 1.35 to 1.46 in four cohorts. It was also associated with a 1.26-fold (95% confidence interval (CI) 1.13–1.41) increased odds of incident major osteoporotic fracture in the Asian population. We demonstrated that gSOS was more predictive of incident major osteoporotic fracture (area under the receiver operating characteristic curve (AUROC) = 0.734; 95% CI 0.727–0.740) and incident hip fracture (AUROC = 0.798; 95% CI 0.791–0.805) than most traditional clinical risk factors, including prior fracture, use of corticosteroids, rheumatoid arthritis, and smoking. We also showed that adding gSOS to the Fracture Risk Assessment Tool (FRAX) could refine the risk prediction with a positive net reclassification index ranging from 0.024 to 0.072.ConclusionsWe generated and validated a PRS for SOS which was associated with the risk of fracture. This score was more strongly associated with the risk of fracture than many clinical risk factors and provided an improvement in risk prediction. gSOS should be explored as a tool to improve risk stratification to identify individuals at high risk of fracture.

Identifying Causes of Fracture Beyond Bone Mineral Density: Evidence From Human Genetics.

New therapies may help to prevent osteoporotic fractures other than through increasing bone mineral density (BMD). Because fracture risk has an important genetic component, we aim to identify loci increasing fracture risk that do not decrease BMD, using a recently-proposed structural equation model adapted to remove genetic influences of BMD on fracture risk. We used summary statistics of the largest genome-wide association studies (GWASs) for BMD and for fracture in these analyses. We next estimated the genetic correlation between the non-BMD or BMD-related genetic effects and other clinical risk factors for fracture. Last, based on white British participants in the UK Biobank, we conducted genetic risk score analyses to assess whether the aggregated genetic effects conferred increased major osteoporotic fracture risk. We found that only three loci affecting fracture risk exhibited genetic effects not mediated by BMD: SOST, CPED1-WNT16, and RSPO3, while these three loci simultaneously conferred BMD-related effects. No strong genetic associations between non-BMD or BMD-related effects and 16 clinical risk factors were observed. However, non-BMD effects might be genetic correlated with hip bone size. In the UK Biobank, a 1 standard deviation (1-SD) increase in the non-BMD genetic risk score conferred an odds ratio of 1.17 for incident major osteoporotic fracture, compared to 1.29 by a BMD-related genetic risk score. Our study suggests that the majority of common genetic predisposition toward fracture risk acts upon BMD. Although non-BMD genetic effects may exist, they are not strongly correlated with most traditional clinical risk factors. Risk loci harboring non-BMD genetic effects may influence other perspectives of bone quality, or confer effects that existing GWASs fail to capture, but they demonstrate weaker impact on fracture risk than BMD-related genetic effects. These findings suggest that most successful drug development programs for osteoporosis should focus on pathways identified through BMD-associated loci. © 2022 American Society for Bone and Mineral Research (ASBMR).

Clinical Application of a Novel Genetic Risk Score for Ischemic Stroke in Patients With Cardiometabolic Disease.

Genome-wide association studies have identified single-nucleotide polymorphisms that are associated with an increased risk of stroke. We sought to determine whether a genetic risk score (GRS) could identify subjects at higher risk for ischemic stroke after accounting for traditional clinical risk factors in 5 trials across the spectrum of cardiometabolic disease. Subjects who had consented for genetic testing and who were of European ancestry from the ENGAGE AF-TIMI 48 (Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation), SOLID-TIMI 52 (Stabilization of Plaques Using Darapladib), SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus), PEGASUS-TIMI 54 (Prevention of Cardiovascular Events in Patients With Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin), and FOURIER (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Patients With Elevated Risk) trials were included in this analysis. A set of 32 single-nucleotide polymorphisms associated with ischemic stroke was used to calculate a GRS in each patient and identify tertiles of genetic risk. A Cox model was used to calculate hazard ratios for ischemic stroke across genetic risk groups, adjusted for clinical risk factors. In 51 288 subjects across the 5 trials, a total of 960 subjects had an ischemic stroke over a median follow-up period of 2.5 years. After adjusting for clinical risk factors, a higher GRS was strongly and independently associated with increased risk for ischemic stroke (P trend=0.009). In comparison with individuals in the lowest third of the GRS, individuals in the middle and top tertiles of the GRS had adjusted hazard ratios of 1.15 (95% CI, 0.98-1.36) and 1.24 (95% CI 1.05-1.45) for ischemic stroke, respectively. Stratification into subgroups revealed that the performance of the GRS appeared stronger in the primary prevention cohort with an adjusted hazard ratio for the top versus lowest tertile of 1.27 (95% CI, 1.04-1.53), in comparison with an adjusted hazard ratio of 1.06 (95% CI, 0.81-1.41) in subjects with previous stroke. In an exploratory analysis of patients with atrial fibrillation and CHA2DS2-VASc score of 2, high genetic risk conferred a 4-fold higher risk of stroke and an absolute risk equivalent to those with CHA2DS2-VASc score of 3. Across a broad spectrum of subjects with cardiometabolic disease, a 32-single-nucleotide polymorphism GRS was a strong, independent predictor of ischemic stroke. In patients with atrial fibrillation but lower CHA2DS2-VASc scores, the GRS identified patients with risk comparable to those with higher CHA2DS2-VASc scores.

Stress Biomarkers Do Not Correlate With Risk Factors for Kidney Injury After Cardiac Surgery

The urinary cell cycle arrest biomarkers (UBs) insulin-like growth factor-binding protein-7 and tissue inhibitor of metalloproteinases-2 provide early detection of kidney stress, and elevations may predict cardiac surgery-associated acute kidney injury (CS-AKI). We sought to determine whether known clinical risk factors for CS-AKI correlated with increased UB values. UBs were measured over a 12-month period the morning after on-pump cardiac surgery. Patients with a preoperative serum creatinine level greater than 2.0 mg/dL or patients undergoing dialysis were excluded. Known clinical AKI risk factors in patients with elevated UB (>0.3 (ng/mL)2/1000), that is known to correlate with kidney stress, were compared with patients with low scores (≤0.3 (ng/mL)2/1000) by using logistic regression; the analysis was repeated with UB as a continuous variable. A total of 412 patients met inclusion criteria. Unadjusted results demonstrated a clinically similar CS-AKI risk profile in patients with either elevated or low UB values. The Pearson correlation between preoperative estimated glomerular filtration rate and UB was low (r= 0.16). Clinical risk factors for CS-AKI were not associated with elevated UB values in the logistic regression model, thus producing an area under the receiver operating characteristic curve of 0.63. Linear regression analysis also found few associations between CS-AKI clinical risk factors and UB when measured as a continuous variable, (R2)= 0.15. Traditional CS-AKI clinical risk factors do not differ between patients with normal or elevated UB values. This UB test may identify patients at increased risk for AKI who otherwise would appear to be at low risk by traditional metrics.

Growth Differentiation Factor 15 and NT-proBNP as Blood-Based Markers of Vascular Brain Injury and Dementia.

BackgroundGDF15 (growth differentiation factor 15) and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) may offer promise as biomarkers for cognitive outcomes, including dementia. We determined the association of these biomarkers with cognitive outcomes in a community‐based cohort.Methods and ResultsPlasma GDF15 (n=1603) and NT‐proBNP levels (n=1590) (53% women; mean age, 68.7 years) were measured in dementia‐free Framingham Offspring cohort participants at examination 7 (1998–2001). Participants were followed up for incident dementia. Secondary outcomes included Alzheimer disease dementia, magnetic resonance imaging structural brain measures, and neurocognitive performance. During a median 11.8‐year follow‐up, 131 participants developed dementia. On multivariable Cox proportional‐hazards analysis, higher circulating GDF15 was associated with an increased risk of incident all‐cause and Alzheimer disease dementia (hazard ratio [HR] per SD increment in natural log‐transformed biomarker value, 1.54 [95% CI, 1.22–1.95] and 1.37 [95% CI, 1.03–1.81], respectively), whereas higher plasma NT‐proBNP was also associated with an increased risk of all‐cause dementia (HR, 1.32; 95% CI, 1.05–1.65). Elevated GDF15 was associated with lower total brain and hippocampal volumes, greater white matter hyperintensity volume, and poorer cognitive performance. Elevated NT‐proBNP was associated with greater white matter hyperintensity volume and poorer cognitive performance. Addition of both biomarkers to a conventional risk factor model improved dementia risk classification (net reclassification improvement index, 0.25; 95% CI, 0.05–0.45).ConclusionsElevated plasma GDF15 and NT‐proBNP were associated with vascular brain injury on magnetic resonance imaging, poorer neurocognitive performance, and increased risk of incident dementia in individuals aged >60 years. Both biomarkers improved dementia risk classification beyond that of traditional clinical risk factors, indicating their potential value in predicting incident dementia.

The prognostic value of ITGA and ITGB superfamily members in patients with high grade serous ovarian cancer

BackgroundDeregulation of integrins signaling had been documented to participate in multiple fundamental biological processes, and the aberrant expression of integrin family members were linked to the prognosis of various cancers. However, the role of integrins in predicting progression and prognosis of ovarian cancer patients are still largely elusive. This study is aimed to explore the prognostic values of ITGA and ITGB superfamily members in high grade serous ovarian cancers (HGSOC).MethodsGSE26712 dataset was used to determine the differential expression of ITGA and ITGB superfamily member between HGSOC and normal counterparts. The Cancer Genome Altas (TGGA) and GSE9891 datasets were used to determine the prognostic values of ITGA and ITGB superfamily members in HGSOC, followed by the development of nomograms predictive of recurrence free survival (RFS) and overall survival (OS).ResultsITGA6 and ITGB5 expression were significantly downregulated in HGSOC compared with that in normal counterparts. In contrast, ITGA2, ITGA5, ITGA7, ITGA8, ITGA9, ITGA10, ITGB3, ITGB4, ITGB6, and ITGB8 were all significantly upregulated in HGSOC compared with that in normal counterparts. Both univariable and multivariable analysis indicated that ITGB1 was associated with extended RFS. The ITGB1-related nomogram indicated that ITGB1 had the largest contribution to RFS, followed by FIGO stage and debulking status. The C-index for predicting RFS was 0.55 (95% CI 0.50–0.59) in TCGA dataset (training dataset) and 0.65 (95% CI 0.59–0.72) in GSE9891 dataset (validation dataset), respectively. Regarding OS, ITGB8 was associated with reduced survival suggested by both univariable and multivariable analysis. ITGA7 appeared to be associated with improved survival though without reaching statistical significance. The ITGA7/ITGB8-based nomogram showed that age at initial diagnosis had the largest contribution to OS, followed by ITGB8 and ITGA7 expression. The C-index for predicting OS was 0.65 (95% CI 0.60–0.69) in TCGA dataset (training dataset) and 0.59 (95% CI 0.51–0.66) in GSE9891 dataset (validation dataset), respectively.ConclusionIn conclusion, ITGB1, ITGA7 and ITGB8 added prognostic value to the traditional clinical risk factors used to assess the clinical outcomes of HGSOC.

Bone fragility in patients with chronic kidney disease.

Mineral and bone diseases (MBD) are predominant in patients with chronic kidney disease (CKD) and lead to several bone manifestations, from pain to skeletal fractures. Cumulative traditional clinical risk factors, such as age and gender, in addition to those related to CKD, enhance the risk of comorbidity and mortality related to fractures. Despite great advances in understanding MBD in CKD, clinical and biological targets are lacking, which leads to under-management of fractures. Optimal PTH control results in a net improvement in defining the levels of bone remodeling. In addition, circulating biomarkers such as bone-specific alkaline phosphatase and cross-linked collagen type I peptide will also provide additional information about remodeling rate, bone mineralization and the evaluation of fracture risk. Imaging techniques identify patients at risk by measurement of bone mineral density by DEXA or by high peripheral QCT, which allow the discrimination of trabecular and cortical bone. Here, we have reviewed the literature related to epidemiology and the pathophysiological role of mineral and biochemical factors involved in CKD-MBD with a special focus on fracture risk. We also provide an algorithm that could be used for the management of bone diseases and to guide treatment decisions. Finally, the combined expertise of clinicians from various disciplines is crucial for the best prevention of fractures.

Clinical risk factors and atherosclerotic plaque extent to define risk for major events in patients without obstructive coronary artery disease: the long-term coronary computed tomography angiography CONFIRM registry

In patients without obstructive coronary artery disease (CAD), we examined the prognostic value of risk factors and atherosclerotic extent. Patients from the long-term CONFIRM registry without prior CAD and without obstructive (≥50%) stenosis were included. Within the groups of normal coronary computed tomography angiography (CCTA) (N = 1849) and non-obstructive CAD (N = 1698), the prognostic value of traditional clinical risk factors and atherosclerotic extent (segment involvement score, SIS) was assessed with Cox models. Major adverse cardiac events (MACE) were defined as all-cause mortality, non-fatal myocardial infarction, or late revascularization. In total, 3547 patients were included (age 57.9 ± 12.1 years, 57.8% male), experiencing 460 MACE during 5.4 years of follow-up. Age, body mass index, hypertension, and diabetes were the clinical variables associated with increased MACE risk, but the magnitude of risk was higher for CCTA defined atherosclerotic extent; adjusted hazard ratio (HR) for SIS >5 was 3.4 (95% confidence interval [CI] 2.3-4.9) while HR for diabetes and hypertension were 1.7 (95% CI 1.3-2.2) and 1.4 (95% CI 1.1-1.7), respectively. Exclusion of revascularization as endpoint did not modify the results. In normal CCTA, presence of ≥1 traditional risk factors did not worsen prognosis (log-rank P = 0.248), while it did in non-obstructive CAD (log-rank P = 0.025). Adjusted for SIS, hypertension and diabetes predicted MACE risk in non-obstructive CAD, while diabetes did not increase risk in absence of CAD (P-interaction = 0.004). Among patients without obstructive CAD, the extent of CAD provides more prognostic information for MACE than traditional cardiovascular risk factors. An interaction was observed between risk factors and CAD burden, suggesting synergistic effects of both.

Polygenic risk for coronary heart disease acts through atherosclerosis in type 2 diabetes

BackgroundType 2 diabetes increases the risk of coronary heart disease (CHD), yet the mechanisms involved remain poorly described. Polygenic risk scores (PRS) provide an opportunity to understand risk factors since they reflect etiologic pathways from the entire genome. We therefore tested whether a PRS for CHD influenced risk of CHD in individuals with type 2 diabetes and which risk factors were associated with this PRS.MethodsWe tested the association of a CHD PRS with CHD and its traditional clinical risk factors amongst individuals with type 2 diabetes in UK Biobank (N = 21,102). We next tested the association of the CHD PRS with atherosclerotic burden in a cohort of 352 genome-wide genotyped participants with type 2 diabetes who had undergone coronary angiograms.ResultsIn the UK Biobank we found that the CHD PRS was strongly associated with CHD amongst individuals with type 2 diabetes (OR per standard deviation increase = 1.50; p = 1.5 × 10− 59). But this CHD PRS was, at best, only weakly associated with traditional clinical risk factors, such as hypertension, hyperlipidemia, glycemic control, obesity and smoking. Conversely, in the angiographic cohort, the CHD PRS was strongly associated with multivessel stenosis (OR = 1.65; p = 4.9 × 10− 4) and increased number of major stenotic lesions (OR = 1.35; p = 9.4 × 10− 3).ConclusionsPolygenic predisposition to CHD is strongly associated with atherosclerotic burden in individuals with type 2 diabetes and this effect is largely independent of traditional clinical risk factors. This suggests that genetic risk for CHD acts through atherosclerosis with little effect on most traditional risk factors, providing the opportunity to explore new biological pathways.

Genetic associations with clozapine-induced myocarditis in patients with schizophrenia

Clozapine is the most effective antipsychotic drug for schizophrenia, yet it can cause life-threatening adverse drug reactions, including myocarditis. The aim of this study was to determine whether schizophrenia patients with clozapine-induced myocarditis have a genetic predisposition compared with clozapine-tolerant controls. We measured different types of genetic variation, including genome-wide single-nucleotide polymorphisms (SNPs), coding variants that alter protein expression, and variable forms of human leucocyte antigen (HLA) genes, alongside traditional clinical risk factors in 42 cases and 67 controls. We calculated a polygenic risk score (PRS) based on variation at 96 different genetic sites, to estimate the genetic liability to clozapine-induced myocarditis. Our genome-wide association analysis identified four SNPs suggestive of increased myocarditis risk (P < 1 × 10−6), with odds ratios ranging 5.5–13.7. The SNP with the lowest P value was rs74675399 (chr19p13.3, P = 1.21 × 10−7; OR = 6.36), located in the GNA15 gene, previously associated with heart failure. The HLA-C*07:01 allele was identified as potentially predisposing to clozapine-induced myocarditis (OR = 2.89, 95% CI: 1.11–7.53), consistent with a previous report of association of the same allele with clozapine-induced agranulocytosis. Another seven HLA alleles, including HLA-B*07:02 (OR = 0.25, 95% CI: 0.05–1.2) were found to be putatively protective. Long-read DNA sequencing provided increased resolution of HLA typing and validated the HLA associations. The PRS explained 66% of liability (P value = 9.7 × 10−5). Combining clinical and genetic factors together increased the proportion of variability accounted for (r2 0.73, P = 9.8 × 10−9). However, due to the limited sample size, individual genetic associations were not statistically significant after correction for multiple testing. We report novel candidate genetic associations with clozapine-induced myocarditis, which may have potential clinical utility, but larger cohorts are required for replication.

Feasibility and Applicability of Wireless Handheld Ultrasound Measurement of Carotid Intima-Media Thickness in Patients with Cardiac Symptoms.

PurposeRoutine screening for carotid intima-media thickness (CIMT) and cardiovascular (CV) disease in asymptomatic patients has been criticized for the high costs and large number of patients required for detecting one patient with coronary artery disease (CAD). In order to overcome the low cost-effectiveness thereof, we investigated the feasibility of an economic wireless handheld ultrasound (WHUS) device for CIMT measurement in symptomatic patients.Materials and MethodsA total of 100 consecutive patients with cardiac symptoms were enrolled. CIMT was measured in all patients. Coronary angiography was performed in 75 patients indicated for the exam.ResultsThe mean of maximal CIMT measured from left/right common carotid artery and bulb (max-CIMT) by the WHUS device showed excellent agreement [intraclass correlation coefficient (ICC)=0.960] with a standard ultrasound device and great interobserver repeatability (ICC>0.9 between all observers). Receiver operating characteristic curve analysis showed that the predictive power for CAD was improved when max-CIMT and plaque information (plaque≥2) was added [area under the curve (AUC): 0.838] to the traditional clinical CV risk factors (AUC: 0.769). The cutoff values for CAD prediction with the standard device and the WHUS device were 1.05 mm (AUC: 0.807, sensitivity: 0.78, specificity: 0.53) and 1.10 mm (AUC: 0.725, sensitivity: 0.98, specificity: 0.27), respectively.Conclusionmax-CIMT measured by a WHUS device showed excellent agreement and repeatability, compared with standard ultrasound. Combined max-CIMT and plaque information added predictive power to the traditional clinical CV risk factors in detecting high-risk CAD patients.

Heart rate fragmentation gives novel insights into non-autonomic mechanisms governing beat-to-beat control of the heart's rhythm.

ObjectivesTo demonstrate how heart rate fragmentation gives novel insights into non-autonomic mechanisms of beat-to-beat variability in cycle length, and predicts survival of cardiology clinic patients, over and above traditional clinical risk factors and measures of heart rate variability.Approach: We studied 2893 patients seen by cardiologists with clinical data including 24-hour Holter monitoring. Novel measures of heart rate fragmentation alongside canonical time and frequency domain measures of heart rate variability, as well as an existing local dynamics score were calculated. A proportional hazards model was utilized to relate the results to survival.Main results: The novel heart rate fragmentation measures were validated and characterized with respect to the effects of age, ectopy and atrial fibrillation. Correlations between parameters were determined. Critically, heart rate fragmentation results could not be accounted for by undersampling respiratory sinus arrhythmia. Increased heart rate fragmentation was associated with poorer survival (p ≪ 0.01 in the univariate model). In multivariable analyses, increased heart rate fragmentation and more abnormal local dynamics (p 0.045), along with increased clinical risk factors (age (p ≪ 0.01), tobacco use (p ≪ 0.01) and history of heart failure (p 0.019)) and lower low- to high-frequency ratio (p 0.022) were all independent predictors of 2-year mortality.Significance: Analysis of continuous ECG data with heart rate fragmentation indices yields information regarding non-autonomic control of beat-to-beat variability in cycle length that is independent of and additive to established parameters for investigating heart rate variability, and predicts mortality in concert with measures of local dynamics, frequency content of heart rate, and clinical risk factors.