Nomenclature for the human Arf family of GTP-binding proteins: ARF, ARL, and SAR proteins

The Ras superfamily is comprised of at least four large families of regulatory guanosine triphosphate–binding proteins, including the Arfs. The Arf family includes three different groups of proteins: the Arfs, Arf-like (Arls), and SARs. Several Arf family members have been very highly conserved throughout eukaryotic evolution and have orthologues in evolutionally diverse species. The different means by which Arf family members have been identified have resulted in an inconsistent and confusing array of names. This confusion is further compounded by differences in nomenclature between different species. We propose a more consistent nomenclature for the human members of the Arf family that may also serve as a guide for nomenclature in other species

A meta-analysis of gene expression signatures of blood pressure and hypertension

Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.Tianxiao Huan, Tõnu Esko, Marjolein J. Peters, Luke C. Pilling, Katharina Schramm, Claudia Schurmann, Brian H. Chen, Chunyu Liu, Roby Joehanes, Andrew D. Johnson, Chen Yao, Sai-xia Ying, Paul Courchesne, Lili Milani, Nalini Raghavachari, Richard Wang, Poching Liu, Eva Reinmaa, Abbas Dehghan, Albert Hofman, André G. Uitterlinden, Dena G. Hernandez, Stefania Bandinelli, Andrew Singleton, David Melzer, Andres Metspalu, Maren Carstensen, Harald Grallert, Christian Herder, Thomas Meitinger, Annette Peters, Michael Roden, Melanie Waldenberger, Marcus Dörr, Stephan B. Felix, Tanja Zeller, International Consortium for Blood Pressure GWAS, ICBP, Ramachandran Vasan, Christopher J. O'Donnell, Peter J. Munson, Xia Yang, Holger Prokisch, Uwe Völker, Joyce B. J. van Meurs, Luigi Ferrucci, Daniel Lev

Different HLA-DRB1 allele distributions in distinct clinical subgroups of sarcoidosis patients

<p>Abstract</p> <p>Background</p> <p>A strong genetic influence by the MHC class II region has been reported in sarcoidosis, however in many studies with different results. This may possibly be caused by actual differences between distinct ethnic groups, too small sample sizes, or because of lack of accurate clinical subgrouping.</p> <p>Subjects and methods</p> <p>In this study we HLA typed a large patient population (n = 754) recruited from one single centre. Patients were sub-grouped into those with Löfgren's syndrome (LS) (n = 302) and those without (non-Löfgren's) (n = 452), and the majority of them were clinically classified into those with recovery within two years (resolving) and those with signs of disease for more than two years (non-resolving). PCR was used for determination of HLA-DRB1 alleles. Swedish healthy blood donors (n = 1366) served as controls.</p> <p>Results</p> <p>There was a dramatic difference in the distribution of HLA alleles in LS compared to non-LS patients (p = 4 × 10^-36). Most notably, DRB1*01, DRB1*03 and DRB1*14, clearly differed in LS and non-LS patients. In relation to disease course, DRB1*07, DRB1*14 and DRB1*15 generally associated with, while DRB1*01 and DRB1*03 protected against, a non-resolving disease. Interestingly, the clinical influence of DRB1*03 (good prognosis) dominated over that of DRB1*15 (bad prognosis).</p> <p>Conclusions</p> <p>We found several significant differences between LS and non-LS patients and we therefore suggest that genetic association studies in sarcoidosis should include a careful clinical characterisation and sub-grouping of patients, in order to reveal true genetic associations. This may be particularly accurate to do in the heterogeneous non-LS group of patients.</p

Helicobacter pylori colonization and obesity - A Mendelian randomization study

Obesity is associated with substantial morbidity, costs, and decreased life expectancy, and continues to rise worldwide. While etiological understanding is needed for prevention, epidemiological studies indicated that colonization with Helicobacter pylori (H. pylori) may affect body mass index (BMI), but with inconsistent results. Here, we examine the relationship between H. pylori colonization and BMI/obesity. Cross-sectional analyses were performed in two independent population-based cohorts of elderly from the Netherlands and Germany (n = 13,044). Genetic risk scores were conducted based on genetic loci associated with either H. pylori colonization or BMI/obesity. We performed a bi-directional Mendelian randomization. Meta-analysis of cross-sectional data revealed no association between anti-H. pylori IgG titer and BMI, nor of H. pylori positivity and BMI. Anti-H. pylori IgG titer was negatively associated with obesity (OR 0.99972; 95% CI 0.99946-0.99997, p = 0.03) and with obesity classes (Beta -6.91 •10-5; 95% CI -1.38•10-4, -5.49•10-7, p = 0.048), but the magnitude of these effects was limited. Mendelian randomization showed no causal relation between H. pylori genetic risk score and BMI/obesity, nor between BMI or obesity genetic risk scores and H. pylori positivity. This study provides no evidence for a clinically relevant association between H. pylori and BMI/obesity

ARF GTPases and their GEFs and GAPs: concepts and challenges

Detailed structural, biochemical, cell biological, and genetic studies of any gene/protein are required to develop models of its actions in cells. Studying a protein family in the aggregate yields additional information, as one can include analyses of their coevolution, acquisition or loss of functionalities, structural pliability, and the emergence of shared or variations in molecular mechanisms. An even richer understanding of cell biology can be achieved through evaluating functionally linked protein families. In this review, we summarize current knowledge of three protein families: the ARF GTPases, the guanine nucleotide exchange factors (ARF GEFs) that activate them, and the GTPase-activating proteins (ARF GAPs) that have the ability to both propagate and terminate signaling. However, despite decades of scrutiny, our understanding of how these essential proteins function in cells remains fragmentary. We believe that the inherent complexity of ARF signaling and its regulation by GEFs and GAPs will require the concerted effort of many laboratories working together, ideally within a consortium to optimally pool information and resources. The collaborative study of these three functionally connected families ( \u3e /=70 mammalian genes) will yield transformative insights into regulation of cell signaling

Thermography imaging during static and controlled thermoregulation in complex regional pain syndrome type 1: diagnostic value and involvement of the central sympathetic system

BACKGROUND: Complex Regional Pain Syndrome type 1 (CRPS1) is a clinical diagnosis based on criteria describing symptoms of the disease. The main aim of the present study was to compare the sensitivity and specificity of calculation methods used to assess thermographic images (infrared imaging) obtained during temperature provocation. The secondary objective was to obtain information about the involvement of the sympathetic system in CRPS1. METHODS: We studied 12 patients in whom CRPS1 was diagnosed according to the criteria of Bruehl. High and low whole body cooling and warming induced and reduced sympathetic vasoconstrictor activity. The degree of vasoconstrictor activity in both hands was monitored using a videothermograph. The sensitivity and specificity of the calculation methods used to assess the thermographic images were calculated. RESULTS: The temperature difference between the hands in the CRPS patients increases significantly when the sympathetic system is provoked. At both the maximum and minimum vasoconstriction no significant differences were found in fingertip temperatures between both hands. CONCLUSION: The majority of CRPS1 patients do not show maximal obtainable temperature differences between the involved and contralateral extremity at room temperature (static measurement). During cold and warm temperature challenges this temperature difference increases significantly. As a result a higher sensitivity and specificity could be achieved in the diagnosis of CRPS1. These findings suggest that the sympathetic efferent system is involved in CRPS1

A highly immunogenic and effective measles virus-based Th1-biased COVID-19 vaccine

The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and has spread worldwide, with millions of cases and more than 1 million deaths to date. The gravity of the situation mandates accelerated efforts to identify safe and effective vaccines. Here, we generated measles virus (MeV)-based vaccine candidates expressing the SARS-CoV-2 spike glycoprotein (S). Insertion of the full-length S protein gene in two different MeV genomic positions resulted in modulated S protein expression. The variant with lower S protein expression levels was genetically stable and induced high levels of effective Th1- biased antibody and T cell responses in mice after two immunizations. In addition to neutralizing IgG antibody responses in a protective range, multifunctional CD8+and CD4+T cell responses with S protein-specific killing activity were detected. Upon challenge using a mouse-adapted SARS-CoV-2, virus loads in vaccinated mice were significantly lower, while vaccinated Syrian hamsters revealed protection in a harsh challenge setup using an early-passage human patient isolate. These results are highly encouraging and support further development of MeV-based COVID-19 vaccines

Grape berry size is a key factor in determining New Zealand Pinot noir wine composition

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand (NZ)’s situation is no exception. To increase the probability of making highly typical PN wines, producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in affordable varietal wine ranges. To understand if higher-yielding vines produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.0 kg per metre of row) and wines of composition comparable to “Icon” labels. Approximately 20 % of 660 grape lots (N = 135) were selected within a narrow juice Total Soluble Solids (TSS) range of 22.0 ± 1.0 °Brix and made into single-vine wines under controlled conditions. Multiple Factor Analysis of the vine, berry, juice and wine parameters from three vintages found grape Berry Weight to be the most effective clustering variable. As the Berry Weight category decreased, there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics and decreased juice amino acids. The influence of berry weight on wine composition would appear stronger than the individual effects of Vintage, Region, Vineyard or vine Yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5 kg per vine, provided that the Leaf Area:Fruit Weight ratio is above 11 cm² per g, mean berry weight is below 1.2 g and juice TSS is above 22 °Brix

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge