Renal Doppler was introduced in the 1980s to screen for renovascular disease and detect renal artery stenosis. 1It was also studied as a potential tool to improve the assessment of renal obstruction or transplant dysfunction. 2 The renal resistive index (RRI) obtained by the Doppler arterial waveform analysis is the most popular measure described in these pathologies. 3 It is a noninvasive and reproducible measure to investigate renal hemodynamics, 4 calculated from the peak systolic and end-diastolic velocities using the following equation: ([peak systolic velocity−end-diastolic velocity]/peak systolic velocity). RRI is based on the changes in flow velocity created by the pulsatile arterial perfusion and can be used as an estimate of renal arterial resistance. For instance, vasomotor stimuli such as sympathetic activation or fluid load can induce changes in the RRI that indirectly reflect changes in the renal vascular resistance.5 Drugs affecting arteriolar vasomotor properties, such as nitroglycerine or captopril, have also been reported to change RRI. 6,7 However, a preserved vascular compliance seems to be necessary for vascular resistance to affect RRI. 8 Hence, with increasing downstream resistance, the diastolic velocity falls relative to systolic value, and RRI increases. In contrast, in the presence of a significant (>70%) main artery stenosis, the diastolic blood flow is less affected, but a slower systole with a dampened waveform (called parvus tardus) is observed, resulting in a decreased RRI value. 9 Even with the widespread use of RRI, reference values and systematic factors influencing measurement values are not well known. Only small-sized studies have evaluated Abstract-Increased renal resistive index (RRI) has been recently associated with target organ damage and cardiovascular or renal outcomes in patients with hypertension and diabetes mellitus. However, reference values in the general population and information on familial aggregation are largely lacking. We determined the distribution of RRI, associated factors, and heritability in a population-based study. Families of European ancestry were randomly selected in 3 Swiss cities. Anthropometric parameters and cardiovascular risk factors were assessed. A renal Doppler ultrasound was performed, and RRI was measured in 3 segmental arteries of both kidneys. We used multilevel linear regression analysis to explore the factors associated with RRI, adjusting for center and family relationships. Sex-specific reference values for RRI were generated according to age. Heritability was estimated by variance components using the ASSOC program (SAGE software). Four hundred women (mean age±SD, 44.9±16.7 years) and 326 men (42.1±16.8 years) with normal renal ultrasound had mean RRI of 0.64±0.05 and 0.62±0.05, respectively (P<0.001). In multivariable analyses, RRI was positively associated with female sex, age, systolic blood pressure, and body mass index. We observed an inverse correlation with diastolic blood pressure and heart rate. Age had a nonli...

BackgroundAlthough the relationship between serum uric acid (SUA) and adiposity is well established, the direction of the causality is still unclear in the presence of conflicting evidences. We used a bidirectional Mendelian randomization approach to explore the nature and direction of causality between SUA and adiposity in a population-based study of Caucasians aged 35 to 75 years.Methods and FindingsWe used, as instrumental variables, rs6855911 within the SUA gene SLC2A9 in one direction, and combinations of SNPs within the adiposity genes FTO, MC4R and TMEM18 in the other direction. Adiposity markers included weight, body mass index, waist circumference and fat mass. We applied a two-stage least squares regression: a regression of SUA/adiposity markers on our instruments in the first stage and a regression of the response of interest on the fitted values from the first stage regression in the second stage. SUA explained by the SLC2A9 instrument was not associated to fat mass (regression coefficient [95% confidence interval]: 0.05 [−0.10, 0.19] for fat mass) contrasting with the ordinary least square estimate (0.37 [0.34, 0.40]). By contrast, fat mass explained by genetic variants of the FTO, MC4R and TMEM18 genes was positively and significantly associated to SUA (0.31 [0.01, 0.62]), similar to the ordinary least square estimate (0.27 [0.25, 0.29]). Results were similar for the other adiposity markers.ConclusionsUsing a bidirectional Mendelian randomization approach in adult Caucasians, our findings suggest that elevated SUA is a consequence rather than a cause of adiposity.

• Renal length and volume are heritable traits, independent of age and size. • Based on a European population, gender-specific reference values/percentiles are provided for renal length. • Renal length correlates positively with body length and weight. • There was no difference between right and left renal lengths in this study. • This negates general teaching that the left kidney is larger and longer.