👤 Paul E Peppard

The origins of periodic leg movements (PLMs), a strong correlate of restless legs syndrome (RLS), are uncertain. This study was performed to assess the relationship between PLMs and peripheral iron deficiency, as measured with ferritin levels corrected for inflammation. We included a cross-sectional sample of a cohort study of 801 randomly selected people (n = 1008 assays, mean age 58.6 ± 0.3 years) from Wisconsin state employee agencies. A previously validated automatic detector was used to measure PLMs during sleep. The patients were categorized into RLS symptoms-positive and RLS symptoms-negative based on a mailed survey response and prior analysis. Analyses were performed using a linear model with PLM category above and below 15 PLM/h (periodic leg movement index, PLMI) as the dependent variable, and adjusting for known covariates, including previously associated single-nucleotide polymorphisms (SNPs) within BTBD9, TOX3/BC034767, MEIS1, MAP2K5/SKOR1, and PTPRD. Ferritin and C-reactive protein (CRP) levels were measured in serum, and ferritin levels corrected for inflammation using CRP levels. After controlling for cofactors, PLMI ≥ 15 was associated with low (≤50 ng/mL) ferritin levels (OR = 1.55, p = 0.020). The best model was found using quasi-least squares regression of ferritin as a function of PLMI, with an increase of 0.0034 PLM/h predicted by a decrease of 1 ng/mL ferritin (p = 0.00447). An association was found between low ferritin and greater PLMs in a general population of older adults, independent of genetic polymorphisms, suggesting a role of low iron stores in the expression of these phenotypes. Patients with high PLMI may require to be checked for iron deficiency. Show less

To examine association between periodic leg movements (PLM) and 13 single nucleotide polymorphisms (SNPs) in 6 loci known to increase risk of restless legs syndrome (RLS). Stanford Center for Sleep Sciences and Medicine and Clinical Research Unit of University of Wisconsin Institute for Clinical and Translational Research. Adult participants (n = 1,090, mean age = 59.7 years) from the Wisconsin Sleep Cohort (2,394 observations, 2000-2012). A previously validated automatic detector was used to measure PLMI. Thirteen SNPs within BTBD9, TOX3/BC034767, MEIS1 (2 unlinked loci), MAP2K5/SKOR1, and PTPRD were tested. Analyses were performed using a linear model and by PLM category using a 15 PLM/h cutoff. Statistical significance for loci was Bonferroni corrected for 6 loci (P < 8.3 × 10(-3)). RLS symptoms were categorized into four groups: likely, possible, no symptoms, and unknown based on a mailed survey response. Prevalence of PLMI ≥ 15 was 33%. Subjects with PLMs were older, more likely to be male, and had more frequent RLS symptoms, a shorter total sleep time, and higher wake after sleep onset. Strong associations were found at all loci except one. Highest associations for PLMI > 15/h were obtained using a multivariate model including age, sex, sleep disturbances, and the best SNPs for each loci, yielding the following odds ratios (OR) and P values: BTBD9 rs3923809(A) OR = 1.65, P = 1.5×10(-8); TOX3/BC034767 rs3104788(T) OR = 1.35, P = 9.0 × 10(-5); MEIS1 rs12469063(G) OR = 1.38, P = 2.0 × 10(-4); MAP2K5/SKOR1 rs6494696(G) OR = 1.24, P = 1.3×10(-2); and PTPRD(A) rs1975197 OR = 1.31, P = 6.3×10(-3). Linear regression models also revealed significant PLM effects for BTBD9, TOX3/BC034767, and MEIS1. Co-varying for RLS symptoms only modestly reduced the genetic associations. Single nucleotide polymorphisms demonstrated to increase risk of RLS are strongly linked to increased PLM as well, although some loci may have more effects on one versus the other phenotype. Show less