Probiotic and selenium co-supplementation, and the effects on clinical, metabolic and genetic status in Alzheimer's disease: A randomized, double-blind, controlled trial

Background and aims: Combined probiotic and selenium supplementation may improve Alzheimer's disease (AD) by correcting metabolic abnormalities, and attenuating inflammation and oxidative stress. This study aimed to determine the effects of probiotic and selenium co-supplementation on cognitive function and metabolic status among patients with AD. Methods: This randomized, double-blind, controlled clinical trial was conducted among 79 patients with AD. Patients were randomly assigned to receive either selenium (200 μg/day) plus probiotic containing Lactobacillus acidophilus, Bifidobacterium bifidum, and Bifidobacterium longum (2 × 109 CFU/day each) (n = 27), selenium (200 μg/day) (n = 26) or placebo (n = 26) for 12 weeks. Results: Selenium supplementation, compared with the placebo, significantly reduced serum high sensitivity C-reactive protein (hs-CRP) (P < 0.001), insulin (P = 0.001), homeostasis model of assessment-insulin resistance (HOMA-IR) (P = 0.002), LDL-cholesterol (P = 0.04) and total-/HDL-cholesterol ratio (P = 0.004), and significantly increased total glutathione (GSH) (P = 0.001) and the quantitative insulin sensitivity check index (QUICKI) (P = 0.01). Compared with only selenium and placebo, probiotic and selenium co-supplementation resulted in a significant increase in mini-mental state examination score (+1.5 ± 1.3 vs. +0.5 ± 1.2 and −0.2 ± 1.1, respectively, P < 0.001). Probiotic plus selenium intake resulted in a significant reduction in hs-CRP (−1.6 ± 1.4 vs. −0.8 ± 1.0 and +0.1 ± 0.5 mg/L, respectively, P < 0.001), and a significant increase in total antioxidant capacity (+89.4 ± 129.6 vs. +20.0 ± 62.5 and −0.7 ± 27.2 mmol/L, respectively, P = 0.001) and GSH (+122.8 ± 136.5 vs. +102.2 ± 135.2 and +1.5 ± 53.2 μmol/L, respectively, P = 0.001) compared with only selenium and placebo. In addition, subjects who received probiotic plus selenium supplements had significantly lower insulin levels (−2.1 ± 2.5 vs. −1.0 ± 1.3 and +0.7 ± 2.0 μIU/mL, respectively, P < 0.001), HOMA-IR (−0.5 ± 0.6 vs. −0.2 ± 0.3 and +0.1 ± 0.4, respectively, P < 0.001), and higher QUICKI (+0.01 ± 0.01 vs. +0.005 ± 0.007 and −0.002 ± 0.01, respectively, P < 0.006) compared with only selenium and placebo. Additionally, probiotic and selenium co-supplementation resulted in a significant reduction in serum triglycerides (−17.9 ± 26.1 vs. −3.5 ± 33.9 and +0.3 ± 9.3 mg/dL, respectively, P = 0.02), VLDL- (−3.6 ± 5.2 vs. −0.7 ± 6.8 and +0.05 ± 1.8 mg/dL, respectively, P = 0.02), LDL- (−8.8 ± 17.8 vs. −8.1 ± 19.2 and +2.7 ± 19.0 mg/dL, respectively, P = 0.04) and total-/HDL-cholesterol (−0.3 ± 0.7 vs. −0.4 ± 0.9 and +0.3 ± 0.6, respectively, P = 0.005) compared with only selenium and placebo. Conclusions: Overall, we found that probiotic and selenium co-supplementation for 12 weeks to patients with AD improved cognitive function and some metabolic profiles. This study was registered in the Iranian website (www.irct.ir) for registration of clinical trial

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

Abstract: The World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis. However, molecular diagnostics to date have focused largely on first-line drugs and predicting susceptibilities in a binary manner (classifying strains as either susceptible or resistant). Here, we used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration (MIC) in 15,211 Mycobacterium tuberculosis clinical isolates from 23 countries across five continents. We identified 492 unique MIC-elevating variants across 13 drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms