Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study.

BACKGROUND: Observational studies have demonstrated an association between decreased vitamin D level and risk of multiple sclerosis (MS); however, it remains unclear whether this relationship is causal. We undertook a Mendelian randomization (MR) study to evaluate whether genetically lowered vitamin D level influences the risk of MS. METHODS AND FINDINGS: We identified single nucleotide polymorphisms (SNPs) associated with 25-hydroxyvitamin D (25OHD) level from SUNLIGHT, the largest (n = 33,996) genome-wide association study to date for vitamin D. Four SNPs were genome-wide significant for 25OHD level (p-values ranging from 6 × 10-10 to 2 × 10-109), and all four SNPs lay in, or near, genes strongly implicated in separate mechanisms influencing 25OHD. We then ascertained their effect on 25OHD level in 2,347 participants from a population-based cohort, the Canadian Multicentre Osteoporosis Study, and tested the extent to which the 25OHD-decreasing alleles explained variation in 25OHD level. We found that the count of 25OHD-decreasing alleles across these four SNPs was strongly associated with lower 25OHD level (n = 2,347, F-test statistic = 49.7, p = 2.4 × 10-12). Next, we conducted an MR study to describe the effect of genetically lowered 25OHD on the odds of MS in the International Multiple Sclerosis Genetics Consortium study, the largest genetic association study to date for MS (including up to 14,498 cases and 24,091 healthy controls). Alleles were weighted by their relative effect on 25OHD level, and sensitivity analyses were performed to test MR assumptions. MR analyses found that each genetically determined one-standard-deviation decrease in log-transformed 25OHD level conferred a 2.0-fold increase in the odds of MS (95% CI: 1.7-2.5; p = 7.7 × 10-12; I2 = 63%, 95% CI: 0%-88%). This result persisted in sensitivity analyses excluding SNPs possibly influenced by population stratification or pleiotropy (odds ratio [OR] = 1.7, 95% CI: 1.3-2.2; p = 2.3 × 10-5; I2 = 47%, 95% CI: 0%-85%) and including only SNPs involved in 25OHD synthesis or metabolism (ORsynthesis = 2.1, 95% CI: 1.6-2.6, p = 1 × 10-9; ORmetabolism = 1.9, 95% CI: 1.3-2.7, p = 0.002). While these sensitivity analyses decreased the possibility that pleiotropy may have biased the results, residual pleiotropy is difficult to exclude entirely. CONCLUSIONS: A genetically lowered 25OHD level is strongly associated with increased susceptibility to MS. Whether vitamin D sufficiency can delay, or prevent, MS onset merits further investigation in long-term randomized controlled trials.

Molecularly Imprinted Polymers in Electrochemical and Optical Sensors.

Molecular imprinting is the process of template-induced formation of specific recognition sites in a polymer. Synthetic receptors prepared using molecular imprinting possess a unique combination of properties such as robustness, high affinity, specificity, and low-cost production, which makes them attractive alternatives to natural receptors. Improvements in polymer science and nanotechnology have contributed to enhanced performance of molecularly imprinted polymer (MIP) sensors. Encouragingly, recent years have seen an increase in high-quality publications describing MIP sensors for the determination of biomolecules, drugs of abuse, and explosives, driving toward applications of this technology in medical and forensic diagnostics. This review aims to provide a focused overview of the latest achievements made in MIP-based sensor technology, with emphasis on research toward real-life applications.

A Mendelian Randomization Study of the Effect of Type-2 Diabetes and Glycemic Traits on Bone Mineral Density.

Type-2 diabetes (T2D) is associated in observational studies with both higher bone mineral density (BMD) and higher fracture risk for given BMD. These relationships may however be confounded by factors such as body mass index (BMI). Here we used Mendelian randomization (MR) to obtain non-confounded estimates of the effect of T2D and glycemic traits on BMD. We identified genetic variants strongly associated with T2D risk (34,840 T2D cases and 114,981 controls) and fasting glucose (133,010 nondiabetic individuals), but not associated with BMI, and determined the effects of these variants on BMD (up to 83,894 individuals). Using these variants as instrumental variables, we found that a genetically-increased risk of T2D increased femoral neck BMD (+0.034 SD in BMD per unit increase in log-odds of T2D [95% CI, 0.001 to 0.067; p = 0.044]). Genetically-increased fasting glucose also increased femoral neck BMD (+0.13 SD in BMD per mmol/L increase in fasting glucose [95% CI, 0.01 to 0.25; p = 0.034]). Similar nonsignificant trends were observed for the effects of T2D and fasting glucose on lumbar spine BMD. Our results indicate that both genetically-increased T2D risk and genetically-increased fasting glucose have weak positive effects on BMD. © 2016 American Society for Bone and Mineral Research.

A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease.

In observational studies, type-2 diabetes (T2D) is associated with an increased risk of coronary heart disease (CHD), yet interventional trials have shown no clear effect of glucose-lowering on CHD. Confounding may have therefore influenced these observational estimates. Here we use Mendelian randomization to obtain unconfounded estimates of the influence of T2D and fasting glucose (FG) on CHD risk. Using multiple genetic variants associated with T2D and FG, we find that risk of T2D increases CHD risk (odds ratio (OR)=1.11 (1.05-1.17), per unit increase in odds of T2D, P=8.8 × 10(-5); using data from 34,840/114,981 T2D cases/controls and 63,746/130,681 CHD cases/controls). FG in non-diabetic individuals tends to increase CHD risk (OR=1.15 (1.00-1.32), per mmol·per l, P=0.05; 133,010 non-diabetic individuals and 63,746/130,681 CHD cases/controls). These findings provide evidence supporting a causal relationship between T2D and CHD and suggest that long-term trials may be required to discern the effects of T2D therapies on CHD risk.

Power spectra reveal the influence of stochasticity on nonlinear population dynamics.

Stochasticity alters the nonlinear dynamics of inherently cycling populations. The power spectrum can describe and explain the impacts of stochasticity. We fitted models to short observed time series of flour beetle populations in the frequency domain, then used a well fitting stochastic mechanistic model to generate detailed predictions of population spectra. Some predicted spectral peaks represent periodic phenomena induced or modified by stochasticity and were experimentally confirmed. For one experimental treatment, linearization theory explained that these peaks represent overcompensatory decay of deviations from deterministic oscillation. In another treatment, stochasticity caused frequent directional phase shifting around a cyclic attractor. This directional phase shifting was not explained by linearization theory and modified the periodicity of the system. If field systems exhibit directional phase shifting, then changing the intensity of demographic or environmental noise while holding constant the structure of the noise can change the main frequency of population fluctuations.