Pasquale Strazzullo

Potassium intake, stroke, and cardiovascular disease a meta-analysis of prospective studies.

Objective To assess the relation between the level of habitual salt intake and stroke or total cardiovascular disease outcome. Design Systematic review and meta-analysis of prospective studies published 1966-2008. Data sources Medline (1966-2008), Embase (from 1988), AMED (from 1985), CINAHL (from 1982), Psychinfo (from 1985), and the Cochrane Library. Review methods For each study, relative risks and 95% confidence intervals were extracted and pooled with a random effect model, weighting for the inverse of the variance. Heterogeneity, publication bias, subgroup, and meta-regression analyses were performed. Criteria for inclusion were prospective adult population study, assessment of salt intake as baseline exposure, assessment of either stroke or total cardiovascular disease as outcome, follow-up of at least three years, indication of number of participants exposed and number of events across different salt intake categories. Results There were 19 independent cohort samples from 13 studies, with 177 025 participants (follow-up 3.5-19 years) and over 11 000 vascular events. Higher salt intake was associated with greater risk of stroke (pooled relative risk 1.23, 95% confidence interval 1.06 to 1.43; P=0.007) and cardiovascular disease (1.14, 0.99 to 1.32; P=0.07), with no significant evidence of publication bias. For cardiovascular disease, sensitivity analysis showed that the exclusion of a single study led to a pooled estimate of 1.17 (1.02 to 1.34; P=0.02). The associations observed were greater the larger the difference in sodium intake and the longer the follow-up. Conclusions High salt intake is associated with significantly increased risk of stroke and total cardiovascular disease. Because of imprecision in measurement of salt intake, these effect sizes are likely to be underestimated. These results support the role of a substantial population reduction in salt intake for the prevention of cardiovascular disease.

Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies

Aims To assess the relationship between duration of sleep and morbidity and mortality from coronary heart disease (CHD), stroke, and total cardiovascular disease (CVD). Methods and results We performed a systematic search of publications using MEDLINE (1966-2009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions. Studies were included if they were prospective, follow-up >3 years, had duration of sleep at baseline, and incident cases of CHD, stroke, or CVD. Relative risks (RR) and 95% confidence interval (CI) were pooled using a random-effect model. Overall, 15 studies (24 cohort samples) included 474 684 male and female participants (follow-up 6.9-25 years), and 16 067 events (4169 for CHD, 3478 for stroke, and 8420 for total CVD). Sleep duration was assessed by questionnaire and incident cases through certification and event registers. Short duration of sleep was associated with a greater risk of developing or dying of CHD (RR 1.48, 95% CI 1.22-1.80, P < 0.0001), stroke (1.15, 1.00-1.31, P = 0.047), but not total CVD (1.03, 0.93-1.15, P = 0.52) with no evidence of publication bias (P = 0.95, P = 0.30, and P = 0.46, respectively). Long duration of sleep was also associated with a greater risk of CHD (1.38, 1.15-1.66, P = 0.0005), stroke (1.65, 1.45-1.87, P < 0.0001), and total CVD (1.41, 1.19-1.68, P < 0.0001) with no evidence of publication bias (P = 0.92, P = 0.96, and P = 0.79, respectively). Conclusion Both short and long duration of sleep are predictors, or markers, of cardiovascular outcomes.

Quantity and Quality of Sleep and Incidence of Type 2 Diabetes A systematic review and meta-analysis

OBJECTIVE To assess the relationship between habitual sleep disturbances and the incidence of type 2 diabetes and to obtain an estimate of the risk. RESEARCH DESIGN AND METHODS We conducted a systematic search of publications using MEDLINE (1955–April 2009), EMBASE, and the Cochrane Library and manual searches without language restrictions. We included studies if they were prospective with follow-up >3 years and had an assessment of sleep disturbances at baseline and incidence of type 2 diabetes. We recorded several characteristics for each study. We extracted quantity and quality of sleep, how they were assessed, and incident cases defined with different validated methods. We extracted relative risks (RRs) and 95% CI and pooled them using random-effects models. We performed sensitivity analysis and assessed heterogeneity and publication bias. RESULTS We included 10 studies (13 independent cohort samples; 107,756 male and female participants, follow-up range 4.2–32 years, and 3,586 incident cases of type 2 diabetes). In pooled analyses, quantity and quality of sleep predicted the risk of development of type 2 diabetes. For short duration of sleep (≤5–6 h/night), the RR was 1.28 (95% CI 1.03–1.60, P = 0.024, heterogeneity P = 0.015); for long duration of sleep (>8–9 h/night), the RR was 1.48 (1.13–1.96, P = 0.005); for difficulty in initiating sleep, the RR was 1.57 (1.25–1.97, P < 0.0001); and for difficulty in maintaining sleep, the RR was 1.84 (1.39–2.43, P < 0.0001). CONCLUSIONS Quantity and quality of sleep consistently and significantly predict the risk of the development of type 2 diabetes. The mechanisms underlying this relation may differ between short and long sleepers.

Prevalence, detection, and management of cardiovascular risk factors in different ethnic groups in south London.

Objective To assess the prevalence of cardiovascular risk factors and their level of detection and management in three ethnic groups. Design Population based survey during 1994 to 1996. Setting Former Wandsworth Health Authority in South London. Subjects 1578 men and women, aged 40 to 59 years; 524 white, 549 of African descent, and 505 of South Asian origin. Main outcome measures Age adjusted prevalence of hypertension, diabetes, obesity, raised serum cholesterol, and smoking. Results Ethnic minorities of both sexes had raised prevalence rates of hypertension and diabetes compared to white people. Age and sex standardised prevalence ratios for hypertension were 2.6 (95% confidence interval 2.1 to 3.2) in people of African descent and 1.8 (1.4 to 2.3) in those of South Asian origin. For diabetes, the ratios were 2.7 (1.8 to 4.0) in people of African descent and 3.8 (2.6 to 5.6) in those of South Asian origin. Hypertension and diabetes were equally common among Caribbeans and West Africans and among South Asian Hindus and Muslims. Prevalence of severe obesity was high overall, but particularly among women of African descent (40% (35% to 45%)). In contrast, raised serum cholesterol and smoking rates were higher among white people. Of hypertensives, 49% (216 of 442) had adequate blood pressure control. Overall, 18% (80 of 442) of hypertensives and 33% (62 of 188) of diabetics were undetected before our survey. Hypertensive subjects of African descent appeared more likely to have been detected (p = 0.034) but less likely to be adequately managed (p = 0.085). Conclusions Hypertension and diabetes are raised two- to threefold in South Asians, Caribbeans, and West Africans in Britain. Detection, management, and control of hypertension has improved, but there are still differences between ethnic groups. Obesity is above the Health of the Nation targets in all ethnic groups, particularly in women of African descent. Preventive and treatment strategies for different ethnic groups in Britain need to consider both cultural differences and underlying susceptibility to different vascular diseases.

SLC2A9 Is a High-Capacity Urate Transporter in Humans

Background Serum uric acid levels in humans are influenced by diet, cellular breakdown, and renal elimination, and correlate with blood pressure, metabolic syndrome, diabetes, gout, and cardiovascular disease. Recent genome-wide association scans have found common genetic variants of SLC2A9 to be associated with increased serum urate level and gout. The SLC2A9 gene encodes a facilitative glucose transporter, and it has two splice variants that are highly expressed in the proximal nephron, a key site for urate handling in the kidney. We investigated whether SLC2A9 is a functional urate transporter that contributes to the longstanding association between urate and blood pressure in man. Methods and Findings We expressed both SLC2A9 splice variants in Xenopus laevis oocytes and found both isoforms mediate rapid urate fluxes at concentration ranges similar to physiological serum levels (200–500 μM). Because SLC2A9 is a known facilitative glucose transporter, we also tested whether glucose or fructose influenced urate transport. We found that urate is transported by SLC2A9 at rates 45- to 60-fold faster than glucose, and demonstrated that SLC2A9-mediated urate transport is facilitated by glucose and, to a lesser extent, fructose. In addition, transport is inhibited by the uricosuric benzbromarone in a dose-dependent manner (K i = 27 μM). Furthermore, we found urate uptake was at least 2-fold greater in human embryonic kidney (HEK) cells overexpressing SLC2A9 splice variants than nontransfected kidney cells. To confirm that our findings were due to SLC2A9, and not another urate transporter, we showed that urate transport was diminished by SLC2A9-targeted siRNA in a second mammalian cell line. In a cohort of men we showed that genetic variants of SLC2A9 are associated with reduced urinary urate clearance, which fits with common variation at SLC2A9 leading to increased serum urate. We found no evidence of association with hypertension (odds ratio 0.98, 95% confidence interval [CI] 0.9 to 1.05, p > 0.33) by meta-analysis of an SLC2A9 variant in six case–control studies including 11,897 participants. In a separate meta-analysis of four population studies including 11,629 participants we found no association of SLC2A9 with systolic (effect size −0.12 mm Hg, 95% CI −0.68 to 0.43, p = 0.664) or diastolic blood pressure (effect size −0.03 mm Hg, 95% CI −0.39 to 0.31, p = 0.82). Conclusions This study provides evidence that SLC2A9 splice variants act as high-capacity urate transporters and is one of the first functional characterisations of findings from genome-wide association scans. We did not find an association of the SLC2A9 gene with blood pressure in this study. Our findings suggest potential pathogenic mechanisms that could offer a new drug target for gout.

Do statins reduce blood pressure?: a meta-analysis of randomized, controlled trials.

A meta-analysis was performed of the effect of 3hydroxy3methylglutaryl-coenzyme A reductase inhibitors (statins) on blood pressure in humans including the randomized, controlled trials of statin therapy (20 trials and 828 patients) in which concomitant antihypertensive treatment (if any) remained unchanged throughout the study. A total of 291 and 272 patients were given a statin or placebo, respectively, in parallel group trials, whereas 265 took part in crossover trials receiving a statin and placebo (or probucol, in 1 trial). Systolic blood pressure was significantly lower in patients on statin than in those on placebo or control hypolipidemic drug (mean difference: −1.9 mm Hg; 95% CI: −3.8 to −0.1). The effect was greater when the analysis was restricted to studies with a baseline systolic blood pressure >130 mm Hg (&Dgr; systolic blood pressure: −4.0; 95% CI: −5.8 to −2.2 mm Hg). There was a trend for lower diastolic blood pressure in patients receiving statin therapy compared with control: −0.9 mm Hg (95% CI: −2.0 to 0.2) overall and −1.2 mm Hg (95% CI: −2.6 to 0.1) in studies with a baseline diastolic blood pressure >80 mm Hg. In general, the higher the baseline blood pressure, the greater the effect of statins on blood pressure (P=0.066 for systolic blood pressure and P=0.023 for diastolic blood pressure). The blood pressure response to statins was unrelated to age, changes in serum cholesterol, or length of the trial. In conclusion, statin therapy has a relatively small but statistically significant and clinically meaningful effect on blood pressure.

Genetic Variation in the Renin–Angiotensin System and Abdominal Adiposity in Men: The Olivetti Prospective Heart Study

Context Angiotensinogen (AGT), angiotensin-converting enzyme (ACE), and angiotensin II receptor type I (AT2R1) are expressed in adipose tissue, but their role in obesity is unknown. Common polymorphisms involve the ACE gene on chromosome 17 (ACE I/D), the AGT gene on chromosome 1, and the AT2R1 receptor gene on chromosome 3. Contribution Among 959 adult Italian men, DD homozygosity in the ACE gene was associated with overweight (odds ratio, 1.82 [95% CI, 1.16 to 2.87]) and abdominal obesity (odds ratio, 1.76 [CI, 1.06 to 2.90]) compared with the genotypes I/D and II. It was also associated with increases in weight over 20 years. Polymorphisms of AGT and AT2R1 were unrelated to measures of body size. Implications These results suggest that the reninangiotensin system plays a role in the development of obesity. The Editors Human obesity is caused by the interaction of genetic predisposition and many environmental and lifestyle factors (1). Although the chromosomal location of a few putative major genes for human obesity has been identified (2-5), the presence of a greater number of minor genes involved in the process of adipogenesis or in the regulation of adipocyte metabolism probably engenders susceptibility to obesity (6). Polymorphism in several obesity candidate genes has been the subject of intensive investigation, but little attention has been paid to the genes encoding for components of the reninangiotensin system. The products of these genes (angiotensinogen [AGT], angiotensin-converting enzyme [ACE], and angiotensin II type 1 [AT2R1] and type II [AT2R2] receptors) are expressed in the adipose tissue in animal models as well as in humans (7-10). Recent experimental studies suggest that adipose tissue in the reninangiotensin system plays a role in adipocyte growth and differentiation through angiotensin II (11, 12). In addition, epidemiologic studies have reported associations between AGT plasma levels (13, 14), plasma renin activity (15, 16), plasma ACE activity (17), and body mass index (BMI). We investigated the relationship of overweight, obesity, and body fat distribution to three common polymorphisms of the reninangiotensin system: intron 16 of the ACE gene on chromosome 17 (18), the M235T polymorphism of the AGT gene in exon 2 on chromosome 1 (19), and the A-to-C polymorphism in the 3-untranslated region at nucleotide 1166 of the AT2R1 gene on chromosome 3 (20). Because the reninangiotensin system plays a fundamental role in blood pressure regulation and in vascular and cardiac modifications, these polymorphisms have been studied with regard to hypertension and cardiovascular disease. Associations have been reported between the AGT M235T and the AT2R1 A1166C variants and hypertension (19-24), as well as among ACE I/D polymorphism, insulin sensitivity (25-27), and the risk for coronary heart and cerebrovascular disease (28, 29). In adult men who attended the 19941995 follow-up examination of the Olivetti Prospective Heart Study, we examined associations between these polymorphic variants and overweight or obesity, body fat distribution, and related metabolic and hemodynamic variables. We also reported longitudinal findings for a subset of participants who were first examined in 1975 and had been followed for 20 years. Methods Study Sample and Procedures We used the DNA bank and the database of the Olivetti Prospective Heart Study, an epidemiologic investigation of cardiovascular risk factors in men working at the Olivetti factories in southern Italy. The procedures of the Olivetti Prospective Heart Study, which began in 1975, have been described in detail elsewhere (30). Between May 1994 and December 1995, we examined 1075 men 25 to 75 years of age. The participants were seen in the morning, after fasting, in a quiet room at the medical center of the Olivetti factories in Pozzuoli and Marcianise, suburbs of Naples, Italy. We obtained anthropometric measurements, performed blood tests, and administered a fixed-sequence questionnaire that assessed demographic information and medical history. Genotyping of the three polymorphisms of the reninangiotensin system was possible in 959 participants. A group of 457 men seen at the 19941995 follow-up visit of the Olivetti Prospective Heart Study had also been examined in 1975; of these, 143 reported being under dietary restriction for various reasons at follow-up examination. Since the Olivetti Prospective Heart Study aims to evaluate spontaneous changes in body mass and blood pressure, this subgroup was excluded from the main analysis. The local ethics committee approved the study protocol, and participants gave informed consent. Anthropometric Measurements Body weight and height were measured on a standard beam-balance scale with an attached ruler. Body weight was measured to the nearest 0.1 kg, and height was measured to the nearest 1 cm; participants wore light indoor clothing and no shoes. Body mass index was calculated as weight in kilograms divided by the square of the height in meters. At the 19941995 examination, but not at the 1975 examination, waist and arm circumferences were also measured. Waist circumference was measured at the umbilicus level as participants stood erect with abdomens relaxed, arms at their sides, and feet together. After the acromion was marked with each participants arm flexed at a 90-degree angle, arm circumference was measured at the midpoint between the acromion and the olecranon with the arm relaxed and hanging just away from the side of the body. The measurements were obtained to the nearest 0.1 cm with a flexible plastic measuring tape. Overweight was defined as a BMI greater than or equal to 27 kg/m2, obesity was defined as a BMI greater than or equal to 30 kg/m2, and abdominal adiposity was defined as a waist circumference greater than 1.00 m. Blood Pressure Measurement Blood pressure was measured after the participant had been sitting upright for at least 10 minutes. Systolic and diastolic (phase V) blood pressure was measured three 2 minutes apart with a random-zero sphygmomanometer (Gelman Hawksley Ltd., Sussex, United Kingdom). The first reading for each type of pressure was discarded, and the average of the second two readings was recorded. Hypertension was defined as a systolic blood pressure 140 mm Hg or greater, a diastolic blood pressure 90 mm Hg or greater, or both, or as current use of antihypertensive drugs. Biochemical Assays After blood pressure was measured, a fasting venous blood sample was taken in the seated position without stasis. The blood specimens were immediately subjected to centrifugation and stored at 70 C until analyzed. Glucose levels were measured by using an automated method (Cobas-Mira, Roche, Italy), and serum insulin concentration was measured by using radioimmunoassay (Insuline Lisophase, Technogenetics, Milan, Italy). Insulin resistance was estimated by homeostasis model assessment using the following formula, as described by Matthews and colleagues (31): fasting serum insulin level (U/mL) fasting serum glucose level (mmol/L)/22.5. Gene Polymorphisms in the ReninAngiotensin System Genomic DNA was isolated from leukocytes with a nonenzymatic, salting-out procedure (32). The ACE I/D polymorphism in intron 16 was typed by using the method of Rigat and associates (33). To address the possibility of mistyping ID heterozygotes as DD homozygotes because of the preferential amplification of the smaller D allele, all samples typed as DD homozygotes were subjected to a second, independent polymerase chain reaction with a primer pair that permits amplification only in the presence of the I allele; this was done by using the method described by Lindpaintner and coworkers (34). The T235 allele of the ATG gene was detected by using the method of Russ and colleagues (35), and the A1166C polymorphism of the AT2R1 gene was tested as described elsewhere (36). Allelic frequencies were estimated by using gene counting, and genotype distribution was tested for HardyWeinberg equilibrium by using chi-square analysis. Statistical Analysis Analysis of variance was used to evaluate differences in quantitative variables according to genotype; analysis of covariance was performed to account for confounders. A nonparametric test (KruskalWallis) was used for variables that were not normally distributed. The interaction between the effects of gene polymorphism and age on the anthropometric indexes and blood pressure was tested by using multiple linear regression analysis. The association of categorical variables with gene polymorphisms was tested by using logistic regression analysis and is expressed as odds ratios and 95% CIs. Results are expressed as the mean SD or as the mean SE, as specified. Two-sided P values and 95% CIs were used to test the statistical significance of between-group differences. Statistical analysis was performed by using SPSS statistical software, version 10.0 (SPSS, Inc., Chicago, Illinois). Role of the Funding Source The funding source had no role in the collection, analysis, or interpretation of the data or in the decision to submit the paper for publication. Results Table 1 summarizes the main characteristics of the participants of the Olivetti Prospective Heart Study at the 19941995 examination. Nine hundred fifty-nine participants were tested for ACE, AGT, and AT2R1 polymorphism. For the ACE I/D polymorphism, 40% (n = 385) had the DD genotype, 45% (n = 431) had the ID genotype, and 15% (n = 143) had the II genotype. For the AGT polymorphism, 31% (n = 297) had the M235M genotype, 48% (n = 460) had the M235T genotype, and 21% (n = 202) had the T235T genotype. For the AT2R1 polymorphism, 54% (n = 518) had the A1166A genotype, 39% (n = 377) had the A1166C genotype, and 7% (n = 64) had the C1166C genotype. All three polymorphisms were in HardyWeinberg equilibrium, showing that the study sample excluded selection pressure for the genotypes under investigation. Table 1. Characteristics of

Application of Framingham risk estimates to ethnic minorities in United Kingdom and implications for primary prevention of heart disease in general practice: cross sectional population based study

Abstract Objective: To compare the 10 year risk of coronary heart disease (CHD), stroke, and combined cardiovascular disease (CVD) estimated from the Framingham equations. Design:Population based cross sectional survey. Setting: Nine general practices in south London. Population: 1386 men and women, age 40-59 years, with no history of CVD (475 white people, 447 south Asian people, and 464 people of African origin), and a subgroup of 1069 without known diabetes, left ventricular hypertrophy, peripheral vascular disease, renal impairment, or target organ damage. Main outcome measures: 10 year risk estimates. Results: People of African origin had the lowest 10 year risk estimate of CHD adjusted for age and sex (7.0%, 95% confidence interval 6.5 to 7.5) compared with white people (8.8%, 8.2 to 9.5) and south Asians (9.2%, 8.6 to 9.9) and the highest estimated risk of stroke (1.7% (1.5 to 1.9), 1.4% (1.3 to 1.6), 1.6% (1.5 to 1.8), respectively). The estimate risk of combined CVD, however, was highest in south Asians (12.5%, 11.6 to 13.4) compared with white people (11.9%, 11.0 to 12.7) and people of African origin (10.5%, 9.7 to 11.2). In the subgroup of 1069, the probability that a risk of CHD 15% would identify risk of combined CVD 20% was 91% in white people and 81% in both south Asians and people of African origin. The use of thresholds for risk of CHD of 12% in south Asians and 10% in people of African origin would increase the probability of identifying those at risk to 100% and 97%, respectively. Conclusion: Primary care doctors should use a lower threshold of CHD risk when treating mild uncomplicated hypertension in people of African or south Asian origin.

Potassium Intake, Stroke, and Cardiovascular Disease

OBJECTIVES The objective of this study was to assess the relation between the level of habitual potassium intake and the incidence of cardiovascular disease (CVD). BACKGROUND Prospective cohort studies have evaluated the relationship between habitual potassium intake and incidence of vascular disease, but their results have not been not entirely consistent. METHODS We performed a systematic search for prospective studies published, without language restrictions (1966 to December 2009). Criteria for inclusion were prospective adult population study, assessment of baseline potassium intake, assessment of vascular events as outcome, and follow-up of at least 4 years. For each study, relative risks (RRs) and 95% confidence intervals (CIs) were extracted and pooled using a random-effect model, weighted for the inverse of the variance. Heterogeneity, publication bias, subgroup, and meta-regression analyses were performed. RESULTS Eleven studies were identified, providing 15 cohort samples that included 247,510 male and female participants (follow-up 5 to 19 years), 7,066 strokes, 3,058 coronary heart disease (CHD) events, and 2,497 total CVD events. Potassium intake was assessed by 24-h dietary recall (n = 2), food frequency questionnaire (n = 6), or 24-h urinary excretion (n = 3). In the pooled analysis, a 1.64-g (42 mmol) per day higher potassium intake was associated with a 21% lower risk of stroke (RR: 0.79; 95% CI: 0.68 to 0.90; p = 0.0007), with a trend toward lower risk of CHD and total CVD that attained statistical significance after the exclusion of a single cohort, based on sensitivity analysis (RR: 0.93; 95% CI: 0.87 to 0.99; p = 0.03 and RR: 0.74; 95% CI: 0.60 to 0.91; p = 0.0037). CONCLUSIONS Higher dietary potassium intake is associated with lower rates of stroke and might also reduce the risk of CHD and total CVD. These results support recommendations for higher consumption of potassium-rich foods to prevent vascular diseases.

Primary aldosteronism: cardiovascular, renal and metabolic implications.

For many years primary aldosteronism was considered a relatively benign form of hypertension. This assumption reflects the primacy accorded to elevated levels of angiotensin in terms of deleterious cardiovascular effects, and the fact that in primary aldosteronism renin and angiotensin levels are low. We now know that primary aldosteronism causes a constellation of cardiovascular, renal and metabolic sequelae which make it far from benign and that these are not merely effects of blood pressure elevation. In primary aldosteronism, tissue damage, on several indices, is higher than in age-, sex- and blood pressure-matched controls, reflecting the ability of inappropriately elevated aldosterone for salt status to produce structural and functional changes over and above those produced by high blood pressure.