Normally, the heart contracts and relaxes to a regular beat. In atrial fibrillation, the upper chambers of the heart beat irregularly, which affects blood flow into the two lower large chambers. This can lead to stroke, heart failure and other heart-related complications.
Atrial fibrillation triggers were first identified in the pulmonary veins. Hence, the isolation of these veins has become one of the standard treatments for atrial fibrillation. Subsequently, other sites in the heart have been found to trigger and/or drive atrial fibrillation, including the superior vena cava (SVC). Notably, patients with arrhythmogenic SVC have long myocardial sleeves (circularly and longitudinally oriented bundles of heart cells) around the SVC and high amplitude electrical potentials within them.
Although these anatomical features in arrhythmogenic SVC all point to the possibility of genetic factors being involved in atrial fibrillation, this topic has remained largely unstudied. Furthermore, findings of genetic studies previously conducted in people of European ancestry could not be generalized and transferred to those of Asian ancestry.
This critical knowledge gap drove a team of researchers from Tokyo Medical and Dental University(TMDU) in Japan to study the clinical and genetic factors associated with atrial fibrillation in an Asian population. The team discovered two variants of single-nucleotide polymorphism (SNP), a variation in a single nucleotide that occurs at a specific position in the genome, which were significantly associated with SVC arrhythmogenicity.
“We found that among six variants identified in a previous genome-wide association study in Japanese patients, SNPs rs2634073 and rs6584555 were associated with SVC arrhythmogenicity,” said Yusuke Ebana, first author of the study.
“We also determined that SVC arrhythmogenicity was conditionally dependent on age, body mass index, and left ventricular ejection fraction,” Ebana added.
To arrive at that conclusion, the research team conducted a meta-analysis of clinical and genetic factors of 2,170 atrial fibrillation patients with and without SVC arrhythmogenicity across three major hospitals in Japan. Surface electrocardiogram and bipolar intracardiac electrograms were continuously monitored. Additionally, a mapping catheter was placed in the SVC to map the circumferential SVC region using computed tomography (CT) or transesophageal echocardiography as a reference. All the patients were followed-up at least every three months.
“The genes closest to the two SVC variants we found were PITX2 and NEURL1, with the former reported as a left-right determinant in cardiac development,” said Tetsushi Furukawa, senior author of the study. “We speculate that the suppression of NEURL1 in SVC patients with the risk genotype could be the cause of arrhythmogenic SVC leading to atrial fibrillation,” Furukawa added.

Tokyo Medical and Dental University (TMDU)
www.tmd.ac.jp/english/press-release/20171018/index.html

Research by Genevan scientists on gene expression and the non-coding genome is a significant breakthrough for the future of personalized medicine.
Geneticists have taken an important step towards true predictive medicine by exploring the links between disease and genetic activity in different tissues. They thus constructed a model, the first step in identifying sequences in the non-coding genome indicating a disease-related pathogenic effect. In a second study, they went even further by associating the risk of developing a disease – in particular schizophrenia, cardiovascular diseases or diabetes – with the variability of the activity of the genome in different types of cells. And their results brought some surprises. Their findings may well revolutionize how each of us, according to his genome, will take care of his health in the future.
These studies are based on data from the international GTEx project, for "Genotype-Tissue Expression", launched in 2010 and co-directed by Professor Emmanouil Dermitzakis, geneticist at the Faculty of Medicine of the University of Geneva (UNIGE) and director of the Health 2030 Genomics Center. The objective of this project was to collect as many tissues as possible from a large number of individuals to understand the effects of genes and their variations. The data published over the last 7 years have allowed scientists worldwide to make considerable progress in analysing genomic variations specific to each of these tissues and predispositions to diseases.
Examining different types of human tissue from hundreds of people has led to a better understanding of how genomic variants – those changes in the spelling of DNA code inherited from our parents – could control how, when, and how many genes are activated and deactivated in different tissues, increasing the risk of developing a wide range of diseases. One of the main discoveries of the GTEx consortium is that the same variant present in multiple tissues may have a different effect depending on the tissue involved. A variant that affects the activity of two genes associated with blood pressure will, for example, have a greater impact on the expression of these genes in the tibial artery, even if the activity of the genes is higher in other tissues. .
To evaluate the influence of variants on gene activity, the researchers perform an analysis called "eQTL". An eQTL – or quantitative locus of expression of the characters – consists of an association between a variant at a specific location of the genome and the level of activity of a gene in a particular tissue. By comparing the eQTLs of different tissues to the genes associated with diseases one can therefore determine which tissues are most related to a disease. But if we can associate a region of the genome with a phenotype (a disease, for example), scientists were not yet able to determine exactly which nucleotide – the bricks of our DNA – when it mutates, contributes to the phenotype. question. Emmanouil Dermitzakis emphasizes as follows: "We needed to design a model to precisely link variants to a particular disease. Our goal, to simplify, was to locate the exact nucleotide that, in case of mutation, increases the risk of a disease, rather than the associated region or gene.
To build a solid model, scientists performed eQTL analyzes of hundreds of samples and identified thousands of causal variations in the non-coding genome. Using this dataset, they began building models to recognize these variations from DNA sequences, without linking them to existing phenotypes. As described by Andrew A. Brown, assistant professor in the Department of Genetic Medicine and Development of UNIGE’s Faculty of Medicine and one of the first authors of these studies: "We wanted to recognize pathogenic variants without any other information than this. sequence. If our model is confirmed, we will solve one of the major problems of modern genomics: by simply reading non-coding DNA sequences, we will be able to identify their pathogenic effects. This is the real future of predictive medicine.

University of Geneva
www.unige.ch/medecine/fr/carrousel/la-lecture-des-variants-genomique-ouvre-la-voie-a-la-medecine-predictive/

A recent study has confirmed that EKF’s  Quo-Test^® A1c point-of-care testing (POCT) analyser shows comparable performance to a lab-based HPLC system for the measurement of glycated hemoglobin (HbA1c). Published in Practical Laboratory Medicine, the study undertaken by the Diabetes Research Unit Cymru, Swansea University, UK, also observed that under the correct circumstances using WHO guidelines Quo-Test is appropriate for the diagnosis of Type 2 diabetes.
HbA1c is routinely used as a measure for the assessment of long-term diabetes control and, more recently, it has also been recommended for diabetes diagnosis. With the increasing use of POCT devices for the measurement of HbA1c without the waiting time associated with laboratory testing, it is crucial to determine how their performance compares. The Swansea University study aimed to compare the Quo-Test POCT analyser using boronate fluorescence quenching technology with an established HPLC laboratory method.
Using whole blood EDTA samples (n=100) from subjects with and without diabetes, the study found good overall agreement between the Quo-Test and reference HPLC method (R2=0.9691; p<0.0001). A diagnostic comparison was also made in line with WHO diagnostic ranges for HbA1c. Use of the Quo-Test as a diagnostic tool, showed 97% (n=79) agreement with the HPLC analyser for glucose intolerance and 100% (n=72) agreement for Type 2 diabetes.
Gareth Dunseath, Diabetes Research Unit Cymru Laboratory Manager, commented, “Device validation and testing is an important part of the research work that the Diabetes Research Unit Cymru laboratory undertakes, especially where the findings can expand on the services that we are able to provide. In this study, our findings showed very good reproducibility and agreement between the Quo-Test and an established laboratory HPLC method across a spectrum of glucose tolerance. This gives the reassurance that the Quo-Test can be used in situations where the immediate result afforded by a POCT method is of benefit, such as screening for eligibility for clinical trials.”
The Diabetes Research Unit Cymru study follows another by scientists from the European Reference Laboratory for Glycohemoglobin. This demonstrated that Quo-Test A1c easily met International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) performance criteria for HbA1c measurement. Meeting the IFCC accepted quality targets (>2 sigma at 10% total allowable error (TAE) at 48 mmol/mol HbA1c) is essential for the effective monitoring of glycemic control in diabetes patients.
EKF’s Quo-Test^® analyser has been designed for easy and reliable HbA1c measurement in a point-of-care setting, such as diabetes clinics and doctors’ surgeries. It is fully automated, measuring glycated hemoglobin from a 4 μL sample taken from a finger prick or venous whole blood. Sample results are available within four minutes and reported in IFCC and DCCT standard units. It is also unaffected by most hemoglobin variants. www.ekfdiagnostics.com

Adenomatous polyposis coli (APC) is a gene whose mutations are associated with a rare, hereditary form of colorectal cancer known as familial adenomatous polyposis. Research led by scientists at the Institut Pasteur and Inserm have recently demonstrated that mutations to this gene do not only lead to the emergence of colon polyps; they also harm the immune system, leaving it unable to tackle inflammation of the colonic mucosa. This dual impact supports the development of cancer.
Familial adenomatous polyposis is an inherited condition characterized, from puberty, by the formation of a very large number of polyps, small growths on the inner surface of the colon and the rectum which can develop into tumours. If left untreated, these polyps may result in colorectal cancer before the age of 40.
Colon cancer is one of the most deadly forms of cancer, and familial adenomatous polyposis currently represents 1% of all cases of colorectal cancer. Those affected by this hereditary disease therefore need close medical supervision.
Research led by scientists from the Institut Pasteur and Inserm recently demonstrated that mutations in the adenomatous polyposis coli (APC) gene, known to be involved in familial adenomatous polyposis, do not only lead to the emergence of colon polyps; they also harm the immune system, leaving it unable to tackle inflammation of the colonic mucosa. This dual impact may favour the development of cancer.
As Andrés Alcover, Head of the Lymphocyte Cell Biology Unit at the Institut Pasteur and last author of the paper, explains, "the APC protein, associated with the microtubule cytoskeleton, has a major effect on the structure and differentiation of intestinal epithelial cells. By disrupting these functions in intestinal cells, APC mutations can lead to the development of tumours."
Scientists already knew that APC mutations could influence the immune system, but they had not yet identified the molecular mechanisms involved and the link with colorectal cancer development. The teams of scientists elucidated how the APC protein activates a particular type of immune cell known as T lymphocytes. "The protein activates T lymphocytes using a factor known as NFAT," continues Andrés Alcover. "Polyposis patients have a mutant version of the gene, which leads to a deficiency in APC protein and could reduce the presence of NFAT in cell nuclei" – thereby preventing lymphocyte activation.
One family of T lymphocytes, known as regulatory T cells, is particularly sensitive to APC mutations. The scientists observed a dysfunction in these regulatory T cells – which are present in large numbers in the intestine – in mice with these mutations that are predisposed to develop polyposis like the patients. This dysfunction leads to a deregulation of the immune system in the intestine and a failure to control local inflammation. "This is the first time that we have characterized at molecular level how mutations in the APC protein affect the immune system, creating favourable conditions for cancer development", emphasizes Andrés Alcover.
These findings suggest that mutations in the APC gene play a dual role in the development of colorectal cancer. Not only do they trigger the development of polyps; they also reduce the action of the immune system, preventing it from controlling gut inflammation. This vicious circle supports the development of cancer.
Institut Pasteur
www.pasteur.fr/en/colon-cancer-apc-protein-affects-immunity-preventing-pre-cancerous-inflammation
 

Women diagnosed with breast cancer may benefit from having the molecular subtype of different cells within their tumours identified, argue two researchers. While breast cancer is often treated as a whole, they discuss the growing consensus that cancer cells within a tumour can have multiple origins and respond variably to treatment. The authors advocate for the development of more accurate diagnostic tests to capture molecular irregularities between tumour cells.
"Breast tumours are moving targets because they are really versatile," says Jun-Lin Guan, Francis Brunning Professor and Chair of the Department of Cancer at the University of Cincinnati College of Medicine and member of the Cincinnati Cancer Center and UC Cancer Institute, who co-authored the paper with postdoctoral fellow Syn Kok Yeo. "If you use a treatment that’s targeting one subtype, which kills one type of breast cancer, often the other kind will actually expand. That defeats the purpose of treatment."
Breast cancer cells differ by the types of molecular markers, some of which are found on their surface, which physicians can test to understand the characteristics of a patient’s cancer and devise the best treatment strategy. For example, women with the HER2+ breast cancer subtype generally have a poorer prognosis than those with the luminal A tumours because of how quickly the cells multiply. Often tumour samples are taken and screened for the most common markers present, but Guan and Yeo’s analysis of human and rodent studies raises the possibility that overlapping subtypes are being missed.
They advocate for diagnostic testing to be combined with single-cell technologies, in which individual cells, rather than a collection, are screened for molecular markers. However, as they currently exist, single-cell approaches are expensive and require specialized expertise, so they would not be realistic for regular patient screenings.
"What we’re talking about is still not widely used in practice–there’s a gap between basic cancer research and the clinics that do the diagnoses," Guan says. "However, single-cell technologies are advancing very quickly, so it’s possible that we can see them being used in the near future."
The researchers put forward that the co-existence of distinct breast cancer subtypes within tumors happens because a fraction of breast cancer cells retain many stem cell-like qualities and thus reserve the capability to easily change. This has been observed in human cancer cells and in rodent studies but has yet to be confirmed in patients. Single-cell analysis could assess whether this problem is common or rare in humans.
EurekAlert
www.eurekalert.org/pub_releases/2017-10/cp-raf101917.php