Identification and analysis of single nucleotide polymorphisms in the myosin VA (MYO5A) gene and its exclusion as the causative gene of the dilute coat colour locus in rabbit

[EN] Classical genetic studies have identified different coat colour loci in rabbit and comparative analyses have established corresponding loci across species. In particular, the rabbit dilute locus is determined by a recessive coat colour mutation that modifies the basic colours influenced by the agouti and extension mutations. In mice, similar phenotypic effects are determined by a similarly named locus. This locus encodes the myosin VA (Myo5a) gene, whose protein product is an unconventional myosin that plays an essential role in melanosome transport in the melanocytes. We selected the same gene as a strong candidate for explaining the dilute coat colour in rabbit. To this end, 1399 bp were re-sequenced, spanning 4 exons out of 41 exons and a portion of intronic regions of the rabbit MYO5A gene to identify polymorphisms that could be useful to confirm or exclude this gene as causative of the rabbit dilute locus. Nine polymorphisms were identified, one of which was used to follow the segregation of the blue and black colours in a Checkered Giant F1 family. The single nucleotide polymorphism (SNP) analysed did not co-segregate with the two colours. These results excluded the MYO5A gene as determinant of the dilute locus in rabbit. The two alleles of this SNP were also present in several other breeds with different coat colours, further indicating that this marker is not associated with the dilute mutation in rabbits. Other candidates should be investigated to identify the causative gene of this locus in rabbit.We thank several rabbit breeders and Associazione Nazionale Coniglicoltori Italiani (ANCI) for their collaboration in the sampling of biological materials. This work was supported by RFO and FAGenomicH project funds from the University of Bologna.Fontanesi, L.; Scotti, E.; Dall'olio, S.; Oulmouden, A.; Russo, V. (2012). Identification and analysis of single nucleotide polymorphisms in the myosin VA (MYO5A) gene and its exclusion as the causative gene of the dilute coat colour locus in rabbit. World Rabbit Science. 20(1):35-41. https://doi.org/10.4995/wrs.2012.1033SWORD354120

Investigation of a short interspersed nuclear element polymorphic site in the porcine vertnin gene: Allele frequencies and association study with meat quality, carcass and production traits in Italian Large White pigs

A 291 bp short interspersed nuclear element (SINE) insertion in the porcine vertnin (VRTN) gene on porcine chromosome 7 was shown to affect vertebral number and several production traits: allele Q (with the insertion) increases vertebral number compared to the wild type allele (WT, without insertion). In this study we genotyped this polymorphism in eight pig breeds (Italian Large White, Italian Duroc, Italian Landrace, Cinta Senese, Mora Romagnola, Casertana, Apulo Calabrese, and Nero Siciliano) and in Italian wild boars to evaluate allele frequency distribution of the two alleles. Allele Q was the most frequent in Italian Landrace and Italian Duroc (0.738 and 0.545, respectively) whereas it was the less frequent in all other breeds and was absent in wild boars. Association study was carried out in two Italian Large White samples. These two groups of animals were constituted by performance tested pigs for which estimated breeding values (EBV) and random residuals (RR) for several traits (average daily gain, back fat thickness, feed: gain ratio, lean cuts and ham weight) were calculated: i) 270 pigs chosen without any criteria (random group), that were also measured for several meat quality traits; ii) 560 gilts with extreme and divergent EBV for back fat thickness. For these animals vertebral number was not available. Results of the association analyses indicated that allele Q was associated with a lower ham weight, confirming indirectly, the negative correlation reported by other studies between vertebral number and this trait. No other trait was associated with the analysed VRTN polymorphism

A genome wide association study for backfat thickness in Italian Large White pigs highlights new regions affecting fat deposition including neuronal genes.

open9noBACKGROUND: Carcass fatness is an important trait in most pig breeding programs. Following market requests, breeding plans for fresh pork consumption are usually designed to reduce carcass fat content and increase lean meat deposition. However, the Italian pig industry is mainly devoted to the production of Protected Designation of Origin dry cured hams: pigs are slaughtered at around 160 kg of live weight and the breeding goal aims at maintaining fat coverage, measured as backfat thickness to avoid excessive desiccation of the hams. This objective has shaped the genetic pool of Italian heavy pig breeds for a few decades. In this study we applied a selective genotyping approach within a population of ~ 12,000 performance tested Italian Large White pigs. Within this population, we selectively genotyped 304 pigs with extreme and divergent backfat thickness estimated breeding value by the Illumina PorcineSNP60 BeadChip and performed a genome wide association study to identify loci associated to this trait. RESULTS: We identified 4 single nucleotide polymorphisms with P≤5.0E-07 and additional 119 ones with 5.0E-07<P≤5.0E-05. These markers were located throughout all chromosomes. The largest numbers were found on porcine chromosomes 6 and 9 (n=15), 4 (n=13), and 7 (n=12) while the most significant marker was located on chromosome 18. Twenty-two single nucleotide polymorphisms were in intronic regions of genes already recognized by the Pre-Ensembl Sscrofa10.2 assembly. Gene Ontology analysis indicated an enrichment of Gene Ontology terms associated with nervous system development and regulation in concordance with results of large genome wide association studies for human obesity. CONCLUSIONS: Further investigations are needed to evaluate the effects of the identified single nucleotide polymorphisms associated with backfat thickness on other traits as a pre-requisite for practical applications in breeding programs. Reported results could improve our understanding of the biology of fat metabolism and deposition that could also be relevant for other mammalian species including humans, confirming the role of neuronal genes on obesity.To June 10, 2013 the paper is labelled as "Highly accessed" on the BMC genomics website http://www.biomedcentral.com/1471-2164/13/583openFontanesi L;Schiavo G;Galimberti G;Calò DG;Scotti E;Martelli PL;Buttazzoni L;Casadio R;Russo VFontanesi L;Schiavo G;Galimberti G;Calò DG;Scotti E;Martelli PL;Buttazzoni L;Casadio R;Russo

COVID-19 in patients with thoracic malignancies (TERAVOLT): first results of an international, registry-based, cohort study

Background: Early reports on patients with cancer and COVID-19 have suggested a high mortality rate compared with the general population. Patients with thoracic malignancies are thought to be particularly susceptible to COVID-19 given their older age, smoking habits, and pre-existing cardiopulmonary comorbidities, in addition to cancer treatments. We aimed to study the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on patients with thoracic malignancies. Methods: The Thoracic Cancers International COVID-19 Collaboration (TERAVOLT) registry is a multicentre observational study composed of a cross-sectional component and a longitudinal cohort component. Eligibility criteria were the presence of any thoracic cancer (non-small-cell lung cancer [NSCLC], small-cell lung cancer, mesothelioma, thymic epithelial tumours, and other pulmonary neuroendocrine neoplasms) and a COVID-19 diagnosis, either laboratory confirmed with RT-PCR, suspected with symptoms and contacts, or radiologically suspected cases with lung imaging features consistent with COVID-19 pneumonia and symptoms. Patients of any age, sex, histology, or stage were considered eligible, including those in active treatment and clinical follow-up. Clinical data were extracted from medical records of consecutive patients from Jan 1, 2020, and will be collected until the end of pandemic declared by WHO. Data on demographics, oncological history and comorbidities, COVID-19 diagnosis, and course of illness and clinical outcomes were collected. Associations between demographic or clinical characteristics and outcomes were measured with odds ratios (ORs) with 95% CIs using univariable and multivariable logistic regression, with sex, age, smoking status, hypertension, and chronic obstructive pulmonary disease included in multivariable analysis. This is a preliminary analysis of the first 200 patients. The registry continues to accept new sites and patient data. Findings: Between March 26 and April 12, 2020, 200 patients with COVID-19 and thoracic cancers from eight countries were identified and included in the TERAVOLT registry; median age was 68·0 years (61·8-75·0) and the majority had an Eastern Cooperative Oncology Group performance status of 0-1 (142 [72%] of 196 patients), were current or former smokers (159 [81%] of 196), had non-small-cell lung cancer (151 [76%] of 200), and were on therapy at the time of COVID-19 diagnosis (147 [74%] of 199), with 112 (57%) of 197 on first-line treatment. 152 (76%) patients were hospitalised and 66 (33%) died. 13 (10%) of 134 patients who met criteria for ICU admission were admitted to ICU; the remaining 121 were hospitalised, but were not admitted to ICU. Univariable analyses revealed that being older than 65 years (OR 1·88, 95% 1·00-3·62), being a current or former smoker (4·24, 1·70-12·95), receiving treatment with chemotherapy alone (2·54, 1·09-6·11), and the presence of any comorbidities (2·65, 1·09-7·46) were associated with increased risk of death. However, in multivariable analysis, only smoking history (OR 3·18, 95% CI 1·11-9·06) was associated with increased risk of death. Interpretation: With an ongoing global pandemic of COVID-19, our data suggest high mortality and low admission to intensive care in patients with thoracic cancer. Whether mortality could be reduced with treatment in intensive care remains to be determined. With improved cancer therapeutic options, access to intensive care should be discussed in a multidisciplinary setting based on cancer specific mortality and patients' preference

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis &lt; 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11&nbsp;years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

The hospital Internal Medicine specialist today: a literature review and strength, weaknesses, opportunity, threats (SWOT) analysis to develop a working proposal

The aim of the paper is to identify the role of the hospital Internal Medicine specialist in the Internal Medicine Unit (IMU) through a clinical and statistical analysis of the patients referred to them by identifying the activities that differentiate them from patients in General Medicine and Emergency Departments, i.e. diagnosis and treatment of complex patient with varying degrees of instability, identifying priorities in the acute problems of co-morbidities. The modified early warning score (MEWS), an internationally validated marker, was chosen to assess and stratify the clinical instability of patients referred to the IMU. A literature review was carried out, and a cut-off score of 3 was chosen to define the critical patients referred to the IMU; a MEWS value of 4 defines the need for transfer to the Intensive Care Unit (ICU) or Intensive Cardiac Care Unit (CCU), considered the primary end point in most of the studies examined. To better characterize the internist’s role today, a strength, weaknesses, opportunity, threats (SWOT) analysis was performed and examined, and commented upon. A total of 101 articles were reviewed and 5 were selected. The case histories relating to the IMU appear to be made up of complex patients with conditions that are, in most cases, acute and unstable. From 10% to 17% of patients present a MEWS of 3 or more that defines a condition of severe clinical instability requiring continuous observation and non-invasive multi-parametric monitoring. From 5% to 7% of cases present a MEWS of 4 or more and therefore require transfer to the ICU/CCU or risk rapid death. Approximately 40% of patients present MEWS of 1-2 and still have disease flare-up, but with a lesser degree of instability; however, these patients could experience a potentially negative disease development if not promptly and properly treated. Approximately 40% of patients have MEWS of 0 and represent the group of fragile patients that cannot be studied, diagnosed or stabilized on an outpatient basis. The critical analysis of the literature review and the SWOT analysis suggest that the two specific hospital internist’s tasks are: i) to stabilize acute, severe and complex patients with multiple pathologies; and ii) to develop etiologically difficult diagnoses in these and in fragile patients who need to be admitted to the hospital because the alternative diagnostic routes, for various reasons, cannot be used

Analysis of SNPs in the KIT gene of cattle with different coat colour patterns and perspectives to use these markers for breed traceability and authentication of beef and dairy products

The identification of the breed of origin of farm animals has recently assumed particular relevance as increasing interests in marketing mono-breed labelled lines of beef and dairy products have created the need to protect them from frauds. In order to develop DNA based breed traceability and authentication protocols, the first step is the identification of breed specific markers with high discriminatory power among breeds. We analysed two single nucleotide polymorphisms identified in exon 2 (g.72779776C>T) and exon 3 (g.72783182A>G) of the KIT gene (a candidate gene for the spotting locus) in seven cattle breeds with different coat colour patterns (Italian Holstein-Friesian, no. = 61; Italian Brown, no. = 60; Italian Simmental, no. = 78; Jersey, no. = 60; Rendena, no. = 51; Reggiana, no. = 128; and Modenese, no. = 52). The two alleles of both SNPs were detected in all analysed breeds making their use unsuitable in breed traceabilty with a deterministic approach. Italian Simmental was almost fixed for the most common alleles (g.72779776C and g.72783182A). Haplotype analysis showed that spotted breeds (Italian Holstein-Friesian and Italian Simmental) had only two haplotypes with one of them ([C:A]) with high frequency (~90% and ~99%, respectively). Analysis of molecular variance (AMOVA) averaged over the two loci indicated that genetic variation between spotted and non-spotted groups of breeds amounted to 25.3% (P<0.05) supporting a possible involvement of the KIT gene in influencing the spotted phenotype, but probably not determining it, as we previously suggested. Pairwise Fst values indicated significant differences between almost all pair of investigated breeds. The high discriminatory power of the analysed SNPs is an important characteristic for the inclusion of these markers in SNP panels useful for breed allocation and traceability based on probabilistic approaches