Effects of sample handling and storage on quantitative lipid analysis in human serum

There is sparse information about specific storage and handling protocols that minimize analytical error and variability in samples evaluated by targeted metabolomics. Variance components that affect quantitative lipid analysis in a set of human serum samples were determined. The effects of freeze-thaw, extraction state, storage temperature, and freeze-thaw prior to density-based lipoprotein fractionation were quantified. The quantification of high abundance metabolites, representing the biologically relevant lipid species in humans, was highly repeatable (with coefficients of variation as low as 0.01 and 0.02) and largely unaffected by 1–3 freeze-thaw cycles (with 0–8% of metabolites affected in each lipid class). Extraction state had effects on total lipid class amounts, including decreased diacylglycerol and increased phosphatidylethanolamine in thawed compared with frozen samples. The effects of storage temperature over 1 week were minimal, with 0–4% of metabolites affected by storage at 4°C, −20°C, or −80°C in most lipid classes, and 19% of metabolites in diacylglycerol affected by storage at −20°C. Freezing prior to lipoprotein fractionation by density ultracentrifugation decreased HDL free cholesterol by 37% and VLDL free fatty acid by 36%, and increased LDL cholesterol ester by 35% compared with fresh samples. These findings suggest that density-based fractionation should preferably be undertaken in fresh serum samples because up to 37% variability in HDL and LDL cholesterol could result from a single freeze-thaw cycle. Conversely, quantitative lipid analysis within unfractionated serum is minimally affected even with repeated freeze-thaw cycles

Defining strawberry shape uniformity using 3D imaging and genetic mapping

Strawberry shape uniformity is a complex trait, influenced by multiple genetic and environmental components. To complicate matters further, the phenotypic assessment of strawberry uniformity is confounded by the difficulty of quantifying geometric parameters ‘by eye’ and variation between assessors. An in-depth genetic analysis of strawberry uniformity has not been undertaken to date, due to the lack of accurate and objective data. Nonetheless, uniformity remains one of the most important fruit quality selection criteria for the development of a new variety. In this study, a 3D-imaging approach was developed to characterise berry shape uniformity. We show that circularity of the maximum circumference had the closest predictive relationship with the manual uniformity score. Combining five or six automated metrics provided the best predictive model, indicating that human assessment of uniformity is highly complex. Furthermore, visual assessment of strawberry fruit quality in a multi-parental QTL mapping population has allowed the identification of genetic components controlling uniformity. A “regular shape” QTL was identified and found to be associated with three uniformity metrics. The QTL was present across a wide array of germplasm, indicating a potential candidate for marker-assisted breeding, while the potential to implement genomic selection is explored. A greater understanding of berry uniformity has been achieved through the study of the relative impact of automated metrics on human perceived uniformity. Furthermore, the comprehensive definition of strawberry shape uniformity using 3D imaging tools has allowed precision phenotyping, which has improved the accuracy of trait quantification and unlocked the ability to accurately select for uniform berries

The Role of Spirituality Healing with Perceptions of the Medical Encounter among Latinos

Little is known about the relationship between spirituality healing and perceptions about the medical encounter among Latinos. To examine the association between spirituality healing and attitudes of self-reported perceptions about the medical encounter. A cross-sectional telephone survey. 3,728 Latinos aged ≥18 years residing in the United States from Wave 1 of the Pew Hispanic Center/Robert Wood Johnson Foundation Latino Health Survey. Dependent variables were ever prayed for healing (yes/no), ever asked others to pray for healing (yes/no), considered important spiritual healing (very vs. somewhat or not important), and ever consulted a ‘curandero’ (folk healer in Latin America) (yes/no). The primary independent variables were feelings about the last time seeing a Doctor (confused by information given, or frustrated by lack of information) and perception of quality of medical care (excellent, good, fair or poor) within the past 12 months. Six percent of individuals reported that they had ever consulted a curandero, 60% prayed for healing, 49% asked others to pray for healing, and 69% considered spiritual healing as very important. In multivariable analyses, feeling confused was associated with increased odds of consulting a curandero (OR = 1.58; 95% CI, 1.02–2.45), praying for healing (OR = 1.30; 95% CI, 1.03–1.64), asking others to pray for healing (OR = 1.29; 95% CI, 1.03–1.62), and considering spiritual healing as very important (OR = 1.30; 95% CI, 1.01–1.66). Feeling frustrated by a lack of information was associated with asking others to pray for healing (OR = 1.29; 95% CI, 1.04–1.60). A better perception of quality of medical care was associated with lower odds of consulting a curandero (OR = 0.83; 95% CI, 0.70–0.98). Feelings about the medical encounter were associated with spirituality healing, praying for healing, and asking others to pray for healing. Feeling confused and perception of poor quality of medical care were associated with consulting a curandero

Leucine-Rich Repeat Kinase 2 Modulates Retinoic Acid-Induced Neuronal Differentiation of Murine Embryonic Stem Cells

Background: Dominant mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are the most prevalent cause of Parkinson’s disease, however, little is known about the biological function of LRRK2 protein. LRRK2 is expressed in neural precursor cells suggesting a role in neurodevelopment. Methodology/Principal Findings: In the present study, differential gene expression profiling revealed a faster silencing of pluripotency-associated genes, like Nanog, Oct4, and Lin28, during retinoic acid-induced neuronal differentiation of LRRK2deficient mouse embryonic stem cells compared to wildtype cultures. By contrast, expression of neurotransmitter receptors and neurotransmitter release was increased in LRRK2+/2 cultures indicating that LRRK2 promotes neuronal differentiation. Consistently, the number of neural progenitor cells was higher in the hippocampal dentate gyrus of adult LRRK2-deficient mice. Alterations in phosphorylation of the putative LRRK2 substrates, translation initiation factor 4E binding protein 1 and moesin, do not appear to be involved in altered differentiation, rather there is indirect evidence that a regulatory signaling network comprising retinoic acid receptors, let-7 miRNA and downstream target genes/mRNAs may be affected in LRRK2deficient stem cells in culture. Conclusion/Significance: Parkinson’s disease-linked LRRK2 mutations that associated with enhanced kinase activity may affect retinoic acid receptor signaling during neurodevelopment and/or neuronal maintenance as has been shown in othe

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.</p

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Study of apo(a) length polymorphism and lipoprotein(a) concentrations in subjects with single or double apo(a) isoforms.

Cardiovascular risk is associated with high lipoprotein(a) (Lp(a)) concentrations and low molecular weight apolipoprotein(a) (apo(a)) isoforms. We studied the relationship between these two biological parameters, particularly in subjects expressing two apo(a) isoforms. Plasma Lp(a) was measured by immunonephelometry in 530 unrelated Caucasian patients at high cardiovascular risk, and apo(a) size determined by immunoblotting using a recombinant standard. Two, one, or no apo(a) isoforms were detected in 258, 270, and 2 subjects, respectively. Lp(a) concentrations showed a non-Gaussian distribution, being higher in the 'double band' than in the 'single band' group (median 0.42 vs. 0.11 g/l, p < 0.0005). Apo(a) size distribution was bimodal, with two frequency peaks at 18 kringles (K) and 27 K. Small size apo(a) isoforms were more frequently found in the 'double band' group, where major isoforms were of lower size than minor isoforms (median 20 vs. 27 K). Regression analysis showed that apo(a) gene length accounted for 33% of Lp(a) variation, with a threshold effect at 20 K, no correlation being found over this value. The minor apo(a) isoform did not significantly influence Lp(a) concentration. These data confirm the relationship between apo(a) size and Lp(a) concentration and suggest that the assessment of cardiovascular risk should take into account the threshold effect at 20 K and the absence of influence of the minor apo(a) isoform