Reduced Cognitive Assessment Scores Among Individuals With Magnetic Resonance Imaging-Detected Vascular Brain Injury

Background and Purpose- Little is known about the association between covert vascular brain injury and cognitive impairment in middle-aged populations. We investigated if scores on a cognitive screen were lower in individuals with higher cardiovascular risk, and those with covert vascular brain injury. Methods- Seven thousand five hundred forty-seven adults, aged 35 to 69 years, free of cardiovascular disease underwent a cognitive assessment using the Digital Symbol Substitution test and Montreal Cognitive Assessment, and magnetic resonance imaging (MRI) to detect covert vascular brain injury (high white matter hyperintensities, lacunar, and nonlacunar brain infarctions). Cardiovascular risk factors were quantified using the INTERHEART (A Global Study of Risk Factors for Acute Myocardial Infarction) risk score. Multivariable mixed models tested for independent determinants of reduced cognitive scores. The population attributable risk of risk factors and MRI vascular brain injury on low cognitive scores was calculated. Results- The mean age of participants was 58 (SD, 9) years; 55% were women. Montreal Cognitive Assessment and Digital Symbol Substitution test scores decreased significantly with increasing age

Cardiovascular risk scoring and magnetic resonance imaging detected subclinical cerebrovascular disease

AIMS: Cardiovascular risk factors are used for risk stratification in primary prevention. We sought to determine if simple cardiac risk scores are associated with magnetic resonance imaging (MRI)-detected subclinical cerebrovascular disease including carotid wall volume (CWV), carotid intraplaque haemorrhage (IPH), and silent brain infarction (SBI). METHODS AND RESULTS: A total of 7594 adults with no history of cardiovascular disease (CVD) underwent risk factor assessment and a non-contrast enhanced MRI of the carotid arteries and brain using a standardized protocol in a population-based cohort recruited between 2014 and 2018. The non-lab-based INTERHEART risk score (IHRS) was calculated in all participants; the Framingham Risk Score was calculated in a subset who provided blood samples (n = 3889). The association between these risk scores and MRI measures of CWV, carotid IPH, and SBI was determined. The mean age of the cohort was 58 (8.9) years, 55% were women. Each 5-point increase (∼1 SD) in the IHRS was associated with a 9 mm3 increase in CWV, adjusted for sex (P \u3c 0.0001), a 23% increase in IPH [95% confidence interval (CI) 9-38%], and a 32% (95% CI 20-45%) increase in SBI. These associations were consistent for lacunar and non-lacunar brain infarction. The Framingham Risk Score was also significantly associated with CWV, IPH, and SBI. CWV was additive and independent to the risk scores in its association with IPH and SBI. CONCLUSION: Simple cardiovascular risk scores are significantly associated with the presence of MRI-detected subclinical cerebrovascular disease, including CWV, IPH, and SBI in an adult population without known clinical CVD

Adipocyte hypertrophy, fatty liver and metabolic risk factors in South Asians: the Molecular Study of Health and Risk in Ethnic Groups (mol-SHARE).

OBJECTIVE: We sought to determine if differences in the distribution and characteristics of adipose tissue between South Asians and white Caucasians account for differences in risk factors for cardiovascular disease. RESEARCH DESIGN AND METHODS: We recruited 108 healthy South Asians (36.8 years) and white Caucasians (34.2 years) within three BMI strata. Body composition, adipocyte size, abdominal fat area, and hepatic adiposity were assessed and related to fasting glucose, insulin, lipids and adiponectin. RESULTS: After adjustment for age, sex, and BMI, South Asians compared to white Caucasians had higher ln fasting insulin (mean difference (MD): 0.44; 95% CI: 0.20-0.69), lower HDL cholesterol (md: -0.13; 95% CI:-0.26 to -0.01), and lower adiponectin (md: -2.38; 95% CI: -3.59 to -1.17). South Asians also had more body fat (md: 2.69; 95% CI: 0.70 to 4.69), lower lean muscle mass (md: -3.25; 95%CI: -5.35 to -1.14), increased waist to hip ratio (md: 0.03; 95% CI: 0.01-0.05), less superficial subcutaneous abdominal adipose tissue (md: -2.94; 95% CI: -5.56 to-0.32), more deep/visceral to superficial adipose tissue ratio (md 0.34; 95% CI: 0.02 to 0.65), and more liver fat (md: 7.43%; 95% CI: 2.30 to 12.55%). Adipocyte area was increased in South Asians compared to white Caucasians (md: 64.26; 95% CI: 24.3 to 104.1) units(2). Adjustment for adipocyte area attenuated the ethnic differences in insulin (md: 0.22; 95% CI: -0.07 to 0.51), HDL (md: -0.01; 95% CI: -0.16 to 0.13) and adiponectin (md: -1.11; 95% CI: -2.61 to 0.39). Adjustment for differences in adipocyte area and fat distribution attenuated the ethnic difference in liver fat (md: 5.19; 95% CI: 0.31 to 10.06). CONCLUSION: South Asians have an increased adipocyte area compared to white Caucasians. This difference accounts for the ethnic differences in insulin, HDL cholesterol, adiponectin, and ectopic fat deposition in the liver

The genetic risk of gestational diabetes in South Asian women

South Asian women are at increased risk of developing gestational diabetes mellitus (GDM). Few studies have investigated the genetic contributions to GDM risk. We investigated the association of a type 2 diabetes (T2D) polygenic risk score (PRS), on its own, and with GDM risk factors, on GDM-related traits using data from two birth cohorts in which South Asian women were enrolled during pregnancy. 837 and 4372 pregnant South Asian women from the SouTh Asian BiRth CohorT (START) and Born in Bradford (BiB) cohort studies underwent a 75-g glucose tolerance test. PRSs were derived using genome-wide association study results from an independent multi-ethnic study (~18% South Asians). Associations with fasting plasma glucose (FPG); 2 hr post-load glucose (2hG); area under the curve glucose; and GDM were tested using linear and logistic regressions. The population attributable fraction (PAF) of the PRS was calculated. Every 1 SD increase in the PRS was associated with a 0.085 mmol/L increase in FPG ([95% confidence interval, CI=0.07–0.10], p=2.85×10(−20)); 0.21 mmol/L increase in 2hG ([95% CI=0.16–0.26], p=5.49×10(−16)); and a 45% increase in the risk of GDM ([95% CI=32–60%], p=2.27×10(−14)), independent of parental history of diabetes and other GDM risk factors. PRS tertile 3 accounted for 12.5% of the population’s GDM alone, and 21.7% when combined with family history. A few weak PRS and GDM risk factors interactions modulating FPG and GDM were observed. Taken together, these results show that a T2D PRS and family history of diabetes are strongly and independently associated with multiple GDM-related traits in women of South Asian descent, an effect that could be modulated by other environmental factors

Associations of cardiometabolic outcomes with indices of obesity in children aged 5 years and younger.

BackgroundChildhood obesity is a world-wide concern due to its growing prevalence and association with cardiometabolic risk factors in childhood and subsequent adult cardiovascular disease. In young pre-school children, there is uncertainty regarding which of the commonly used anthropometric measures of childhood obesity is best associated with cardiometabolic risk factors. This study compared the utility of common measures used in identifying obesity in these young children.MethodsThe four commonly used metrics for identifying obesity in children: body fat percentage ≥ 90th percentile, waist circumference ≥ 90th percentile, BMI z score > 2 SD and waist-to-height ratio (WHtR) ≥ 0.5, were measured in a cohort of children born singleton, at full term and followed from birth (n = 761) to 5 years of age (n = 513). The utility of each in identifying cardiometabolic risk factors (fasting lipid profile, fasting blood glucose and blood pressure) was examined.ResultsAt age 5 years, children with percent body fat ≥ 90th percentile or waist circumference ≥ 90th percentile, were associated with higher levels of triglycerides, glucose, and systolic and diastolic blood pressures than those 2 SD was associated with higher levels of triglycerides and systolic and diastolic blood pressure but not glucose at age 5 years. Differences in HDL cholesterol, fasting glucose and systolic blood pressure were observed in children with BMI z score > 2 SD at age 3 years but not with the other indices of obesity. As almost all children had WHtR ≥ 0.5 at birth, ages 1 and 3 years, this measure could not differentiate increased cardiometabolic risk. At age 5 years, the differences were much more obvious, with significant differences in triglycerides and systolic and diastolic blood pressures between those with WHtR ≥ 0.5 and those with ConclusionEach of the four commonly used measures of childhood obesity shows moderate associations with cardiometabolic risk factors at 5 years, with no advantage of one measure over the other. These associations were less consistent at 3 years of age or younger. These observations have not been reported previously

BMI: Body Mass Index, error bars represent the standard error.

<p>BMI: Body Mass Index, error bars represent the standard error.</p

Adipose and lean tissue characteristics of participants.

<p>* Means (± SE) are adjusted for age and BMI,</p><p>† Means (± SE) are adjusted for age, sex and BMI,</p><p>|| Total fat area refers to: superficial + deep+visceral fat by MRI,</p><p>‡ p<0.05 comparing South Asians to Europeans overall,</p><p>§ p<0.05 comparing South Asian women to European women,</p><p>¶ p<0.05 comparing South Asian men to European men,</p><p>Note: There was no change in the IMCL change after adjustment for peak exercise capacity i.e. Vo2 max at 15 mins.</p

Baseline characteristics of participants.

<p>* Means (± SE) are adjusted for age,</p><p>† Means (± SE) are adjusted for age, sex, BMI ‡ p<0.05 comparing South Asians to Europeans overall,</p><p>§ p<0.05 comparing South Asian women to European women,</p><p>|| p<0.05 comparing South Asian men to European men; Physical activity score derived from the SHARE activity index (14).</p

HDL: High Density Lipoprotein, CRP: C-reactive protein.

<p>HDL: High Density Lipoprotein, CRP: C-reactive protein.</p