Prevalence of metabolic syndrome in patients with psoriasis: a cross-sectional study in Singapore

INTRODUCTIONPsoriasis is a chronic inflammatory condition that affects the skin and joints, and is associated with cardiovascular risk factors, including metabolic syndrome (MetS). We aimed to assess the prevalence of MetS in patients with psoriasis and determine whether there was a correlation between psoriasis severity and MetS in a Singapore population.METHODSThis was a cross-sectional study of patients with psoriasis, aged 18–69 years, who attended a tertiary dermatology referral centre in Singapore from October 2007 to February 2009. Fasting glucose, lipids, blood pressure, Psoriasis Area and Severity Index, and body mass index were measured. MetS was diagnosed in the presence of three or more criteria of the modified National Cholesterol Education Program Adult Treatment Panel III.RESULTSAmong 338 patients with psoriasis, there were 238 (70.4%) men and 100 (29.6%) women, who were Chinese (n = 228; 67.5%), Malay (n = 52; 15.4%) and Indian (n = 58; 17.2%). The prevalence of MetS was 45.1%. MetS was 44% more prevalent in patients older than 50 years (p = 0.02). Malay patients with psoriasis were significantly more likely to have hypertriglyceridaemia, elevated fasting plasma glucose and abdominal obesity. There was no significant correlation between psoriasis severity and risk of MetS.CONCLUSIONThe prevalence of MetS in patients with psoriasis in Singapore was 45.1%, or nearly threefold higher than the Singapore general population. Patients with psoriasis should be screened yearly for MetS and any modifiable cardiovascular risk factors should be actively controlled.     

Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.     

Nanomedicines: From Bench to Bedside and Beyond

Advancing nanomedicines from concept to clinic requires integration of new science with traditional pharmaceutical development. The medical and commercial success of nanomedicines is greatly facilitated when those charged with developing nanomedicines are cognizant of the unique opportunities and technical challenges that these products present. These individuals must also be knowledgeable about the processes of clinical and product development, including regulatory considerations, to maximize the odds for successful product registration. This article outlines these topics with a goal to accelerate the combination of academic innovation with collaborative industrial scientists who understand pharmaceutical development and regulatory approval requirements—only together can they realize the full potential of nanomedicines for patients.