The Effect of Alpha-Cyclodextrin on Postprandial Glucose Excursions: a Systematic Meta-Analysis.

Alpha-cyclodextrin (αCD) is a bacterial product that is widely used as a food ingredient. In the European Union (EU), αCD is regulated as a dietary fiber with an authorized health claim "for contributing to the reduction of postprandial glycemic responses." In the US, αCD is generally recognized as save (GRAS), but on April 25, 2022, the U.S. Food and Drug Administration (FDA) rejected the inclusion of αCD in the list of dietary fibers because "the strength of the scientific evidence does not support a finding of a beneficial effect of αCD on postprandial blood glucose …" To evaluate the strength of this scientific evidence, this meta-analysis reviews clinical trials conducted to test the effect of αCD on the rise of blood glucose and insulin levels during three hours after consumption of a meal comprising carbohydrates, fats, and proteins. Several issues related to the standardization of the outcomes, the choice of the statistical methods in the cross-over studies conducted, and the choice of methods for the aggregation of P-values are discussed. It is concluded that the administration of αCD not only reduces the postprandial glycemic responses, but the absence of an increase in insulin levels suggests that αCD acts independently of increasing insulin production and, thus, the beneficial effect of αCD is not affected by insulin resistance.

The First Three Months of COVID-19: Epidemiological Evidence for Two SARS-CoV-2 Strains Spreading and Implications for Prevention Strategies.

About a month after the COVID-19 epidemic peaked in Mainland China and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) migrated to Europe and then the USA, the epidemiological data began to provide important insights into the risks associated with the disease and the effectiveness of intervention strategies such as travel restrictions and lockdowns ("social distancing"). Respiratory diseases, including the 2003 severe acute respiratory syndrome (SARS) epidemic, remain only about two months in any given population, although peak incidence and lethality can vary. The epidemiological data suggested that at least two strains of SARS-CoV-2 had evolved during the first months of the epidemic while the virus migrated from Mainland China to Europe. South Korea (SK), Iran, Italy (IT), and Italy's neighbors were then hit by the more dangerous "SKII" variant. While the first epidemic in continental Asia was about to end and in Europe about to level off, the more recent epidemic in the younger US population was still increasing, albeit not exponentially anymore. The same models that help us to understand the epidemic also help us to choose prevention strategies. The containment of high-risk people, such as the elderly with comorbidities, and reducing disease severity, by either vaccination, reduction of comorbidities (seen as risk factors already in Italy), or early treatment of complications, are the best strategies against a respiratory virus disease (RVD). Lockdowns can be effective during the month following the peak incidence of infections when the exponential increase of cases ends (the window of opportunity). From the standard susceptible-infectious-resistant (SIR) model used, containing low-risk people too early, instead, merely prolongs the time the virus needs to circulate until the incidence is high enough to reach "herd immunity." Containing low-risk people too late is also not helpful, unless to prevent a rebound if containment started too early.

Correction: Complex polymorphisms in endocytosis genes suggest alpha-cyclodextrin as a treatment for breast cancer.

[This corrects the article DOI: 10.1371/journal.pone.0199012.].

Complex polymorphisms in endocytosis genes suggest alpha-cyclodextrin as a treatment for breast cancer.

Most breast cancer deaths are caused by metastasis and treatment options beyond radiation and cytotoxic drugs, which have severe side effects, and hormonal treatments, which are or become ineffective for many patients, are urgently needed. This study reanalyzed existing data from three genome-wide association studies (GWAS) using a novel computational biostatistics approach (muGWAS), which had been validated in studies of 600-2000 subjects in epilepsy and autism. MuGWAS jointly analyzes several neighboring single nucleotide polymorphisms while incorporating knowledge about genetics of heritable diseases into the statistical method and about GWAS into the rules for determining adaptive genome-wide significance. Results from three independent GWAS of 1000-2000 subjects each, which were made available under the National Institute of Health's "Up For A Challenge" (U4C) project, not only confirmed cell-cycle control and receptor/AKT signaling, but, for the first time in breast cancer GWAS, also consistently identified many genes involved in endo-/exocytosis (EEC), most of which had already been observed in functional and expression studies of breast cancer. In particular, the findings include genes that translocate (ATP8A1, ATP8B1, ANO4, ABCA1) and metabolize (AGPAT3, AGPAT4, DGKQ, LPPR1) phospholipids entering the phosphatidylinositol cycle, which controls EEC. These novel findings suggest scavenging phospholipids as a novel intervention to control local spread of cancer, packaging of exosomes (which prepare distant microenvironment for organ-specific metastases), and endocytosis of ß1 integrins (which are required for spread of metastatic phenotype and mesenchymal migration of tumor cells). Beta-cyclodextrins (ßCD) have already been shown to be effective in in vitro and animal studies of breast cancer, but exhibits cholesterol-related ototoxicity. The smaller alpha-cyclodextrins (αCD) also scavenges phospholipids, but cannot fit cholesterol. An in-vitro study presented here confirms hydroxypropyl (HP)-αCD to be twice as effective as HPßCD against migration of human cells of both receptor negative and estrogen-receptor positive breast cancer. If the previous successful animal studies with ßCDs are replicated with the safer and more effective αCDs, clinical trials of adjuvant treatment with αCDs are warranted. Ultimately, all breast cancer are expected to benefit from treatment with HPαCD, but women with triple-negative breast cancer (TNBC) will benefit most, because they have fewer treatment options and their cancer advances more aggressively.

The Ontology of Clinical Research (OCRe): an informatics foundation for the science of clinical research.

To date, the scientific process for generating, interpreting, and applying knowledge has received less informatics attention than operational processes for conducting clinical studies. The activities of these scientific processes - the science of clinical research - are centered on the study protocol, which is the abstract representation of the scientific design of a clinical study. The Ontology of Clinical Research (OCRe) is an OWL 2 model of the entities and relationships of study design protocols for the purpose of computationally supporting the design and analysis of human studies. OCRe's modeling is independent of any specific study design or clinical domain. It includes a study design typology and a specialized module called ERGO Annotation for capturing the meaning of eligibility criteria. In this paper, we describe the key informatics use cases of each phase of a study's scientific lifecycle, present OCRe and the principles behind its modeling, and describe applications of OCRe and associated technologies to a range of clinical research use cases. OCRe captures the central semantics that underlies the scientific processes of clinical research and can serve as an informatics foundation for supporting the entire range of knowledge activities that constitute the science of clinical research.

From single-SNP to wide-locus: genome-wide association studies identifying functionally related genes and intragenic regions in small sample studies.

BACKGROUND: Genome-wide association studies (GWAS) have had limited success when applied to complex diseases. Analyzing SNPs individually requires several large studies to integrate the often divergent results. In the presence of epistasis, multivariate approaches based on the linear model (including stepwise logistic regression) often have low sensitivity and generate an abundance of artifacts. METHODS: Recent advances in distributed and parallel processing spurred methodological advances in nonparametric statistics. U-statistics for structured multivariate data (µStat) are not confounded by unrealistic assumptions (e.g., linearity, independence). RESULTS: By incorporating knowledge about relationships between SNPs, µGWAS (GWAS based on µStat) can identify clusters of genes around biologically relevant pathways and pinpoint functionally relevant regions within these genes. CONCLUSION: With this computational biostatistics approach increasing power and guarding against artifacts, personalized medicine and comparative effectiveness will advance while subgroup analyses of Phase III trials can now suggest risk factors for adverse events and novel directions for drug development.

Ontology-based federated data access to human studies information.

Human studies are one of the most valuable sources of knowledge in biomedical research, but data about their design and results are currently widely dispersed in siloed systems. Federation of these data is needed to facilitate large-scale data analysis to realize the goals of evidence-based medicine. The Human Studies Database project has developed an informatics infrastructure for federated query of human studies databases, using a generalizable approach to ontology-based data access. Our approach has three main components. First, the Ontology of Clinical Research (OCRe) provides the reference semantics. Second, a data model, automatically derived from OCRe into XSD, maintains semantic synchrony of the underlying representations while facilitating data acquisition using common XML technologies. Finally, the Query Integrator issues queries distributed over the data, OCRe, and other ontologies such as SNOMED in BioPortal. We report on a demonstration of this infrastructure on data acquired from institutional systems and from ClinicalTrials.gov.

Clinical symptoms of skin, nails, and joints manifest independently in patients with concomitant psoriasis and psoriatic arthritis.

This study correlated assessment tools for evaluating the severity of skin, nail, and joint symptoms in patients with psoriasis (Pso) and psoriatic arthritis (PsA). Adults with plaque Pso (with or without PsA) were enrolled from four U.S. institutions. Patients were evaluated using a novel 10-area Linear Psoriasis Area and Severity Index (XL-PASI), Psoriatic Arthritis Assessment (PsAA), Psoriatic Arthritis Screening and Evaluation Questionnaire (PASE), Nail Assessment (NA) and Joint Assessment (JA) tools, Psoriasis Weighted Extent and Severity Index (PWESI), and Lattice Physician Global Assessment (LS-PGA). Correlations between assessment tools and individual items in the assessment tools were performed. Data from 180 patients (55 with PsA) were analyzed. Highest correlations between tools (r = 0.77-0.88) were between the XL-PASI, PWESI and LS-PGA. Individual items in the XL-PASI correlated with items in the PWESI for extent skin symptoms, but not for all body areas. Overall, correlations were seen between hands and feet, between face and scalp, and between buttocks, chest, and back. Only low correlation was seen between items assessing joint symptoms with items assessing skin symptoms. These data support the notion that the complex phenotype of psoriatic disease requires instruments that assess the severity of skin, nails, and joints separately.

Hyaluronidase and hyaluronan in insect venom allergy.

BACKGROUND: Insect venoms contain an allergen hyaluronidase that catalyzes the hydrolysis of hyaluronan (HA), a polymer of disaccharide GlcUA-GlcNAc in skin. HAs depending on their size have variable function in inflammation and immunity. This paper reports on whether hyaluronidase, HA polymers and oligomers can promote antibody response in mice. METHODS: HA oligomers (8- to 50-mer; 3-20 kDa) were obtained by bee venom hyaluronidase digestion of HA polymers (750- to 5,000-mer; 300-2,000 kDa). Antibody responses in mice were compared following 3 biweekly subcutaneous injection of ovalbumin (OVA) with or without test adjuvant. RESULTS: OVA-specific IgG1 levels were approximately 2 times higher in BALB/c and C3H/HeJ mice receiving OVA and HA oligomer or polymer than those treated with OVA alone, and no increase in total IgE level was observed. In C57Bl/6 mice, observed increases in IgG1 and IgE were 3.5- and 1.7-fold, respectively, for the oligomer and 16- and 5-fold (p < 0.05), respectively, for the polymer. CONCLUSION: Hyaluronidase by its action on HA in skin can function indirectly as adjuvant to promote IgE and IgG1 response in mice. Insect venoms also have cytolytic peptides and phospholipases with inflammatory roles. These activities found in mice may contribute to venom allergenicity in susceptible people.

Evaluation metrics for biostatistical and epidemiological collaborations.

Increasing demands for evidence-based medicine and for the translation of biomedical research into individual and public health benefit have been accompanied by the proliferation of special units that offer expertise in biostatistics, epidemiology, and research design (BERD) within academic health centers. Objective metrics that can be used to evaluate, track, and improve the performance of these BERD units are critical to their successful establishment and sustainable future. To develop a set of reliable but versatile metrics that can be adapted easily to different environments and evolving needs, we consulted with members of BERD units from the consortium of academic health centers funded by the Clinical and Translational Science Award Program of the National Institutes of Health. Through a systematic process of consensus building and document drafting, we formulated metrics that covered the three identified domains of BERD practices: the development and maintenance of collaborations with clinical and translational science investigators, the application of BERD-related methods to clinical and translational research, and the discovery of novel BERD-related methodologies. In this article, we describe the set of metrics and advocate their use for evaluating BERD practices. The routine application, comparison of findings across diverse BERD units, and ongoing refinement of the metrics will identify trends, facilitate meaningful changes, and ultimately enhance the contribution of BERD activities to biomedical research.

Algal docosahexaenoic acid affects plasma lipoprotein particle size distribution in overweight and obese adults.

Fish oils containing both EPA and DHA have been shown to have beneficial cardiovascular effects, but less is known about the independent effects of DHA. This study was designed to examine the effects of DHA on plasma lipid and lipoprotein concentrations and other biomarkers of cardiovascular risk in the absence of weight loss. In this randomized, controlled, double-blind trial, 36 overweight or obese adults were treated with 2 g/d of algal DHA or placebo for 4.5 mo. Markers of cardiovascular risk were assessed before and after treatment. In the DHA-supplemented group, the decrease in mean VLDL particle size (P ≤ 0.001) and increases in mean LDL (P ≤ 0.001) and HDL (P ≤ 0.001) particle sizes were significantly greater than changes in the placebo group. DHA supplementation also increased the concentrations of large LDL (P ≤ 0.001) and large HDL particles (P = 0.001) and decreased the concentrations of small LDL (P = 0.009) and medium HDL particles (P = 0.001). As calculated using NMR-derived data, DHA supplementation reduced VLDL TG (P = 0.009) and total TG concentrations (P = 0.006). Plasma IL-10 increased with DHA supplementation to a greater extent than placebo (P = 0.021), but no other significant changes were observed in glucose metabolism, insulin sensitivity, blood pressure, or markers of inflammation with DHA. In summary, DHA supplementation resulted in potentially beneficial changes in some markers of cardiometabolic risk, whereas other markers were unchanged.

Nonparametric methods for molecular biology.

In 2003, the completion of the Human Genome Project (1) together with advances in computational resources (2) were expected to launch an era where the genetic and genomic contributions to many common diseases would be found. In the years following, however, researchers became increasingly frustrated as most reported 'findings' could not be replicated in independent studies (3). To improve the signal/noise ratio, it was suggested to increase the number of cases to be included to tens of thousands (4), a requirement that would dramatically restrict the scope of personalized medicine. Similarly, there was little success in elucidating the gene-gene interactions involved in complex diseases or even in developing criteria for assessing their phenotypes. As a partial solution to these enigmata, we here introduce a class of statistical methods as the 'missing link' between advances in genetics and informatics. As a first step, we provide a unifying view of a plethora of nonparametric tests developed mainly in the 1940s, all of which can be expressed as u-statistics. Then, we will extend this approach to reflect categorical and ordinal relationships between variables, resulting in a flexible and powerful approach to deal with the impact of (1) multiallelic genetic loci, (2) poly-locus genetic regions, and (3) oligo-genetic and oligo-genomic collaborative interactions on complex phenotypes.

The human studies database project: federating human studies design data using the ontology of clinical research.

Human studies, encompassing interventional and observational studies, are the most important source of evidence for advancing our understanding of health, disease, and treatment options. To promote discovery, the design and results of these studies should be made machine-readable for large-scale data mining, synthesis, and re-analysis. The Human Studies Database Project aims to define and implement an informatics infrastructure for institutions to share the design of their human studies. We have developed the Ontology of Clinical Research (OCRe) to model study features such as design type, interventions, and outcomes to support scientific query and analysis. We are using OCRe as the reference semantics for federated data sharing of human studies over caGrid, and are piloting this implementation with several Clinical and Translational Science Award (CTSA) institutions.

In vitro and in vivo evidence that thrombospondin-1 (TSP-1) contributes to stirring- and shear-dependent activation of platelet-derived TGF-beta1.

Thrombospondin 1 (TSP-1), which is contained in platelet alpha-granules and released with activation, has been shown to activate latent TGF-beta1 in vitro, but its in vivo role is unclear as TSP-1-null (Thbs1(-/-)) mice have a much less severe phenotype than TGF-beta1-null (Tgfb1(-/-)) mice. We recently demonstrated that stirring and/or shear could activate latent TGF-beta1 released from platelets and have now studied these methods of TGF-beta1 activation in samples from Thbs1(-/-) mice, which have higher platelet counts and higher levels of total TGF-beta1 in their serum than wild type mice. After either two hours of stirring or shear, Thbs1(-/-) samples demonstrated less TGF-beta1 activation (31% and 54% lower levels of active TGF-beta1 in serum and platelet releasates, respectively). TGF-beta1 activation in Thbs1(-/-) mice samples was normalized by adding recombinant human TSP-1 (rhTSP-1). Exposure of platelet releasates to shear for one hour led to near depletion of TSP-1, but this could be prevented by preincubating samples with thiol-reactive agents. Moreover, replenishing rhTSP-1 to human platelet releasates after one hour of stirring enhanced TGF-beta1 activation. In vivo TGF-beta1 activation in carotid artery thrombi was also partially impaired in Thbs1(-/-) mice. These data indicate that TSP-1 contributes to shear-dependent TGF-beta1 activation, thus providing a potential explanation for the inconsistent in vitro data previously reported as well as for the differences in phenotypes of Thbs1(-/-) and Tgfb1(-/-) mice.

Atherosclerosis in survivors of Kawasaki disease.

OBJECTIVES: To test the hypothesis that long-term survivors of low-risk Kawasaki disease (KD) have ongoing vascular inflammation and dysfunction and a higher risk of accelerated atherosclerosis than healthy control subjects. STUDY DESIGN: Twenty-eight patients with KD (7-20 years after acute illness) and 27 age-matched healthy control subjects were examined for medical and dietary history, serum markers of atherosclerotic risk and inflammation, carotid intimal-medial thickness (CIMT) with vascular ultrasound scanning and arterial stiffness with applanation tonometry. RESULTS: Patients and control subjects were similar in age, sex, body mass index, waist-to-hip ratio, blood pressure, cigarette smoking, family history, diet, high-density lipoprotein cholesterol level, lipoprotein (a) level, homocysteine level, glucose level, insulin level, CIMT, arterial stiffness, C-reactive protein level, and inflammatory cytokine level. Levels of total cholesterol and apolipoprotein B were significantly higher in patients with KD than in control subjects. CONCLUSIONS: There was no evidence of increased atherosclerosis. Small but significant differences in cholesterol and apolipoprotein B levels could suggest increased future risk for atherosclerosis and warrant further study.

An extension to a statistical approach for family based association studies provides insights into genetic risk factors for multiple sclerosis in the HLA-DRB1 gene.

BACKGROUND: Multiple sclerosis (MS) is a complex trait in which genes in the MHC class II region exert the single strongest effect on genetic susceptibility. The principal MHC class II haplotype that increases MS risk in individuals of Northern European descent are those that bear HLA-DRB1*15. However, several other HLA-DRB1 alleles have been positively and negatively associated with MS and each of the main allelotypes is composed of many sub-allelotypes with slightly different sequence composition. Given the role of this locus in antigen presentation it has been suggested that variations in the peptide binding site of the allele may underlie allelic variation in disease risk. METHODS: In an investigation of 7,333 individuals from 1,352 MS families, we assessed the nucleotide sequence of HLA-DRB1 for any effects on disease susceptibility extending a recently published method of statistical analysis for family-based association studies to the particular challenges of hyper-variable genetic regions. RESULTS: We found that amino acid 60 of the HLA-DRB1 peptide sequence, which had previously been postulated based on structural features, is unlikely to play a major role. Instead, empirical evidence based on sequence information suggests that MS susceptibility arises primarily from amino acid 13. CONCLUSION: Identifying a single amino acid as a major risk factor provides major practical implications for risk and for the exploration of mechanisms, although the mechanism of amino acid 13 in the HLA-DRB1 sequence's involvement in MS as well as the identity of additional variants on MHC haplotypes that influence risk need to be uncovered.

STUDYING TRAVEL-RELATED INDIVIDUAL ASSESSMENTS AND DESIRES BY COMBINING HIERARCHICALLY STRUCTURED ORDINAL VARIABLES.

Ordinal measures are frequently encountered in travel behavior research. This paper presents a new method for combining them when a hierarchical structure of the data can be presumed. This method is applied to study the subjective assessment of the amount of travel by different transportation modes among a group of French clerical workers, along with the desire to increase or decrease the use of such modes. Some advantages of this approach over traditional data reduction technique such as factor analysis when applied to ordinal data are then illustrated. In this study, combining evidence from several variables sheds light on the observed moderately negative relationship between the personal assessment of the amount of travel and the desire to increase or decrease it, thus integrating previous partial (univariate) results. We find a latent demand for travel, thus contributing to clarify the behavioral mechanisms behind the induced traffic phenomenon. Categorizing the above relationship by transportation mode shows a desire for a less environmental-friendly mix of modes (i.e. a greater desire to use heavy motorized modes and a lower desire to use two-wheeled modes), whenever the respondents do not feel to travel extensively. This result, combined with previous theoretical investigations concerning the determinants of the desire to alter trips consumption levels, shows the importance of making people aware of how much they travel.

Phenotyping genetic diseases using an extension of mu-scores for multivariate data.

As the field of genomics matures, more complex genotypes and phenotypes are being studied. Fanconi anemia (FA), for example, is an inherited chromosome instability syndrome with a complex array of variable disease phenotypes including congenital malformations, hematological manifestations, and cancer. To better understand specific aspects of the genetic etiology of FA and other rare diseases with complex phenotypes, it is often necessary to reduce the dimensions of the disease phenotype information. Towards this end, we extend a novel non-parametric approach to include information about a hierarchical structure among disease phenotypes. The proposed extension increases information content of the phenotype scores obtained and, thereby, the power of genotype-phenotype relationships studies.

A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus.

The analysis of patient blood transcriptional profiles offers a means to investigate the immunological mechanisms relevant to human diseases on a genome-wide scale. In addition, such studies provide a basis for the discovery of clinically relevant biomarker signatures. We designed a strategy for microarray analysis that is based on the identification of transcriptional modules formed by genes coordinately expressed in multiple disease data sets. Mapping changes in gene expression at the module level generated disease-specific transcriptional fingerprints that provide a stable framework for the visualization and functional interpretation of microarray data. These transcriptional modules were used as a basis for the selection of biomarkers and the development of a multivariate transcriptional indicator of disease progression in patients with systemic lupus erythematosus. Thus, this work describes the implementation and application of a methodology designed to support systems-scale analysis of the human immune system in translational research settings.