Objective. The frequency of many adverse events (AEs) associated with low-dose glucocorticoid use is unclear. We sought to determine the prevalence of glucocorticoid-associated AEs in a large US managed care population. Methods. Using linked administrative and pharmacy claims, adults receiving >60 days of glucocorticoids were identified. These individuals were surveyed about glucocorticoid use and symptoms of 8 AEs commonly attributed to glucocorticoid use. Results. Of the 6,517 eligible glucocorticoid users identified, 2,446 (38%) returned the mailed survey. Respondents were 29% men with a mean ؎ SD age of 53 ؎ 14 years; 79% were white and 13% were African American. Respondents had a mean ؎ SD of 7 ؎ 3 comorbid conditions and were prescribed a mean ؎ SD prednisone-equivalent dosage of 16 ؎ 14 mg/day. More than 90% of individuals reported at least 1 AE associated with glucocorticoid use; 55% reported that at least 1 AE was very bothersome. Weight gain was the most common self-reported AE (70% of the individuals), cataracts (15%) and fractures (12%) were among the most serious. After multivariable adjustment, all AEs demonstrated a strong dose-dependent association with cumulative glucocorticoid use. Among users of low-dose therapy (<7.5 mg of prednisone per day), increasing duration of use was significantly associated with acne, skin bruising, weight gain, and cataracts. Conclusion. The prevalence of 8 commonly attributed self-reported glucocorticoid-associated AEs was significantly associated with cumulative and average glucocorticoid dose in a dose-dependent fashion. Physicians should be vigilant for glucocorticoid-related AEs and should counsel patients about possible risks, even among low-dose long-term users.

To investigate whether functional polymorphisms exist in the C-reactive protein (CRP) gene, i.e., ones that contribute directly to differences in baseline CRP among individuals, we sequenced a 1,156-nucleotide-long stretch of the CRP gene promoter in 287 ostensibly healthy people. We identified two single-nucleotide polymorphisms (SNPs), a bi-allelic one at nucleotide -409 (G-->A), and a tri-allelic one at -390 (C-->T-->A), both resident within the hexameric core of transcription factor binding E-box elements. Electrophoretic mobility shift assays confirmed that the SNP within the sequence (-412)CACGTG(-407) (E-box 1) modulates transcription factor binding, and that the one within (-394)CACTTG(-389) (E-box 2) supports transcription factor binding only when the -390 T allele is present. The commonest of four E-box 1/E-box 2 haplotypes (-409G/-390T) identified in the population supported highest promoter activity in luciferase reporter assays, and the rarest one (-409A/-390T) supported the least. Importantly, serum CRP in people with these haplotypes reproduced this rank order, i.e., people with the -409G/-390T haplotype had the highest baseline serum CRP (mean +/- SEM 10.9 +/- 2.25 microg/ml) and people with the -409A/-390T haplotype had the lowest (5.01 +/- 1.56 microg/ml). Furthermore, haplotype-associated differences in baseline CRP were not due to differences in age, sex, or race, and were still apparent in people with no history of smoking. At least two other SNPs in the CRP promoter lie within E-box elements (-198 C-->T, E-box 4, and -861 T-->C, E-box 3), indicating that not only is the quality of E-box sites in CRP a major determinant of baseline CRP level, but also that the number of E-boxes may be important. These data confirm that the CRP promoter does encode functional polymorphisms, which should be considered when baseline CRP is being used as an indicator of clinical outcome. Ultimately, development of genetic tests to screen for CRP expression variants could allow categorization of healthy people into groups at high versus low future risk of inflammatory disease.

Although mathematical relationships can be proven by deductive logic, biological relationships can only be inferred from empirical observations. This is a distinct disadvantage for those of us who strive to identify the genes involved in complex diseases and quantitative traits. If causation cannot be proven, however, what does constitute sufficient evidence for causation? The philosopher Karl Popper said, "Our belief in a hypothesis can have no stronger basis than our repeated unsuccessful critical attempts to refute it." We believe that to establish causation, as scientists, we must make a serious attempt to refute our own hypotheses and to eliminate all known sources of bias before association becomes causation. In addition, we suggest that investigators must provide sufficient data and evidence of their unsuccessful efforts to find any confounding biases. In this editorial, we discuss what "causation" means in the context of complex diseases and quantitative traits, and we suggest guidelines for steps that may be taken to address possible confounders of association before polymorphisms may be called "causative."

A diet low in sodium, alcohol, and protein is associated with lower systolic blood and pulse pressure. Potassium intake was associated with lower systolic and diastolic blood pressure, whereas alcohol intake was associated with lower diastolic blood pressure. In addition, the age-related changes in systolic blood pressure were attenuated by higher calcium and protein intakes. Magnesium was not associated with any changes in blood pressure.

The transmission/disequilibrium (TD) test (TDT), proposed, by Spielman et al., for binary traits is a powerful method for detection of linkage between a marker locus and a disease locus, in the presence of allelic association. As a test for linkage disequilibrium, the TDT makes the assumption that any allelic association present is due to linkage. Allison proposed a series of TD-type tests for quantitative traits and calculated their power, assuming that the marker locus is the disease locus. All these tests assume that the observations are independent, and therefore they are applicable, as a test for linkage, only for nuclear-family data. In this report, we propose a regression-based TD-type test for linkage between a marker locus and a quantitative trait locus, using information on the parent-to-offspring transmission status of the associated allele at the marker locus. This method does not require independence of observations, thus allowing for analysis of pedigree data as well, and allows adjustment for covariates. We investigate the statistical power and validity of the test by simulating markers at various recombination fractions from the disease locus.