genome

Researchers at the Icahn School of Medicine at Mount Sinai have applied a novel machine learning method to identify 413 genetic associations with schizophrenia across 13 brain regions.

As described in the February issue of Nature Genetics, examining gene expression at the tissue level allowed researchers to not only identify new genes associated with schizophrenia, but also pinpoint the areas of the brain in which abnormal expression might occur.

While affecting less than two percent of the global population, schizophrenia is one of the leading causes of disability worldwide. Despite its low prevalence, the disease has major public health and socioeconomic impact, primarily due to hospital readmission and treatment costs. What’s more, while it is widely believed that numerous genes contribute to increased risk of schizophrenia development, the exact genetic underpinnings are poorly understood.

Nonetheless, such ambiguity serves as fuel for many researchers, as the discovery of disease-associated genes is crucial for understanding the mechanisms involved in any illness. Accordingly, Mount Sinai researchers used genome-wide association study findings coupled with transcriptomic imputation to identify schizophrenia-associated disease with tissue-level resolution.

Genome-wide association studies are an increasingly common study type in biomedical research; they look at differences at various points in a genetic code to see whether a variation is found more often in those with a particular trait, such as schizophrenia.

Transcriptomic imputation is a novel machine learning technique that allows researchers to test associations between disease and gene expression in otherwise inaccessible tissues, such as those of the brain.

In the largest study of its kind, 40,299 people with schizophrenia and 62,264 matched controls were studied. The researchers discovered that genes associated with schizophrenia are expressed throughout development: some during specific stages of pregnancy, and others during adolescence or adulthood. They also learned that different regions of the brain confer different risks for schizophrenia, with most associations coming from the dorsolateral prefrontal cortex.

“Our new predictor models gave us unprecedented power to study predicted gene expression in schizophrenia, and to identify new risk genes associated with the disease,” said Laura Huckins, PhD, Assistant Professor of Genetics and Genomic Sciences, and Psychiatry, at the Icahn School of Medicine at Mount Sinai. “In particular, it was fascinating to see schizophrenia risk genes expressed throughout development, including in early pregnancy.”

“By laying the groundwork for combining transcriptomic imputation and genome-wide association study findings, our hope is to not only elucidate gene development as it relates to schizophrenia, but also shape the future of research methods and design.”

CRISPR-Chip enables digital detection of DNA without amplification

Keck Graduate Institute (KGI) Assistant Professor and University of California, Berkeley Visiting Scientist Kiana Aran is the first to combine the power of CRISPR’s nucleic acid targeting with the ultra sensitivity of graphene, making it possible to digitally detect DNA without amplification.

“The innovation is to bring the two together as a capture mechanism. Our system does not use amplification; instead it relies on CRISPR’s genome-searching capability and graphene’s sensitivity,” explains Aran, who led the multi-university research team responsible for the work described in the paper “CRISPR-Chip: A CRISPR-based Graphene-enhanced Field Effect Biosensor for Electronic Detection of Unamplified Target Genes,” which was published in the journal Nature Biomedical Engineering on 25th March 2019.

Aran’s novel system immobilises the CRISPR complexes on the surface of graphene-based transistors. These complexes search a genome to find their target sequence and, if the search is successful, bind to its DNA. This binding changes the conductivity of the graphene material in the transistor, which detects the change using a handheld reader developed by Aran’s industry partner, San Diego-based Cardea Bio.

“What Kiana does is an application we hadn’t thought about before – that no one thought about before. It shows the potential of a graphene biosensor that no one knew was even possible,” says Brett Goldsmith, Cardea’s chief technology officer and co-founder. “To detect DNA without amplification is so shocking, so futuristic. This will skip several generations of technology development.”

Aran and her research colleagues demonstrated the system’s effectiveness by testing for the digital detection of DNA mutations in Duchenne Muscular Dystrophy, a genetic disorder that results in progressive muscle degeneration and shortened life expectancy.

“We have shown that our system is sufficient for genetic mutation testing. Now we need to enhance the system to detect infections,” says Aran. “We’re also evaluating CRISPR-Chip for detection of single-point mutations.”

Aran notes that the system, which enables users to run a test in less than an hour, has potential applications beyond diagnostics. She explains that these include multiplexing capabilities to run hundreds or thousands of tests at the same time. Another potential application is for quality control purposes within companies that use CRISPR for therapeutics; the system could enable them to better evaluate the efficiency of the CRISPR technology.

“I look at everything through the lens of electronics. It’s important to think about electronic biosensors because that is where I believe biological analysis is heading,” says Aran, who is now exploring avenues to commercialise the system. “My goal is to integrate fast-growing electronics technologies with modern biology not only to develop better diagnostic tools, but also to gain a better understanding of biological events using nanoscale electronics devices.”

plant

Researchers at the RIKEN Center for Sustainable Resource Science (CSRS) in Japan have developed a new computational mass-spectrometry system for identifying metabolomes – entire sets of metabolites for different living organisms.

When the new method was tested on select tissues from 12 plant species, it was able to note over 1,000 metabolites. Among them were dozens that had never been found before, including those with antibiotic and anti-cancer potential.

In addition to facilitating the screening of plant-specialised metabolomes, the new process could speed up the discovery of natural products that could be used in medicines, according to the team.

Hiroshi Tsugawa, one of the lead researchers, said: “I believe that computationally decoding metabolomic mass spectrometry data is linked to a deeper understanding of all metabolisms. Our next goal is to improve this methodology to facilitate global identification of human and microbiota metabolomes as well. Newly found metabolites can then be further investigated via genomics, transcriptomics, and proteomics.”

The common pain reliever aspirin (acetylsalicylic acid) was first made in the 19th century and is famously derived from willow bark extract. After a new method of synthesis was discovered and used for almost 70 years, scientists were finally able to understand how it works. This was a long historical process.

There are millions of plant species and each has its own metabolome – the set of all products of the plant’s metabolism. Currently, we only know about 5 percent of all these natural products. Although mass spectrometry can identify plant metabolites, it only works for determining if a sample contains a given molecule.

Computational mass spectrometry is a growing research field that focuses on finding previously unknown metabolites and predicting their functions. The field has established metabolome databases and repositories, which facilitate global identification of human, plant, and microbiota metabolomes.

Led by Hiroshi Tsugawa and Kazuki Saito, a team at CSRS has spent several years developing a system that can quickly identify large numbers of plant metabolites, including those that have not been identified before.

As Tsugawa explains, “while no software can comprehensively identify all the metabolites in a living organism, our program incorporates new techniques in computational mass spectrometry and provides 10 times the coverage of previous methods.” In tests, while mass spectrometry-based methods only noted about 100 metabolites, the team’s new system was able to find more than 1,000.

The new computational technique relies on new algorithms that compare the mass spectrometry outputs from plants that are labeled with carbon-13 with those that are not. The algorithms can predict the molecular formula of the metabolites and classify them by type. They can also predict the substructure of unknown metabolites, and based on similarities in structure, link them to known metabolites, which can help predict their functions.

In particular, the system was able to characterise a class of antibiotics (benzoxazinoids) in rice and maize as well as a class with anti-inflammatory and antibacterial properties (glycoalkaloids) in the common onion, tomato, and potato. It was also able to identify two classes of anti-cancer metabolites, one (triterpene saponins) in soy beans and liquorice, and the other (beta-carboline alkaloid) in a plant from the coffee family.

car-t-cells

A pre-clinical study led by scientists at the University of California Los Angeles Jonsson Comprehensive Cancer Center suggests that heating solid tumours during CAR T-cell therapy can enhance the treatment’s success.

The researchers found that when a heating technique called photothermal ablation was combined with the infusion of CAR T cells, it suppressed melanoma tumour growth for up to 20 days in mice. Among the mice that were treated with the combination, 33 percent were still tumour free after the 20-day mark.

T cells that have been genetically engineered with chimeric antigen receptor, or CAR, have successfully been used to treat many patients with lymphoma and leukaemia. But CAR T-cell therapy has been less successful for treating solid tumours because the tumours have a protective micro environment, which makes it harder for the CAR T cells to break into the tumour and keep the T cells activated.

The UCLA scientists decided to test whether combining CAR T therapy with photothermal therapy could overcome that obstacle.

Photothermal therapy is a minimally invasive technique that uses heat from laser energy to kill cancer cells; it is already being used to treat a variety of cancers and other medical conditions.

The researchers tested a mild hyperthermia of about 40°C to see if it could help enhance the CAR T cells to better attack the tumour.

The UCLA-led team tested the technique in mice that were injected with human melanoma tumours. A photothermal agent was injected into the tumours and then irradiated with the laser to heat them. Then, CAR T cells were injected intravenously. Raising the temperature of the laser to about 40°C helped expand blood vessels associated with the tumour, enhancing T-cell growth.

By enhancing the power of CAR T-cell therapy, the technique could eventually improve the prognosis for people with hard-to-treat solid tumours. The researchers will continue testing the strategy in animals to optimise the heating duration and temperature before determining whether it can be tested on humans.

The research’s co-senior author is Zhen Gu and it is published in the journal Advanced Materials.

Scientists home in on microRNA processing for novel cancer therapies

More than a decade of research on the mda-7/IL-24 gene has shown that it helps to suppress a majority of cancer types, and now scientists are focusing on how the gene drives this process by influencing microRNAs.

Published in March in the journal Proceedings of the National Academy of Sciences, the findings could potentially have implications beyond cancer for a variety of cardiovascular and neurodegenerative diseases caused by the same microRNA-driven processes.

The study was led by Paul B. Fisher, M.Ph., Ph.D., F.N.A.I., Thelma Newmeyer Corman Endowed Chair in Cancer Research and member of the Cancer Molecular Genetics research program at Virginia Commonwealth University Massey Cancer Center, chairman of the Department of Human and Molecular Genetics at VCU School of Medicine and director of the VCU Institute of Molecular Medicine (VIMM).

The mda-7/IL-24 gene was originally discovered by Fisher. He and his colleagues have since published a number of studies detailing how the gene can suppress cancer by directly influencing two important mediators of cell death known as apoptosis and toxic autophagy. They have also been developing mda-7/IL-24 viral gene therapies, purified protein treatments and T-cell-delivered therapies that take advantage of these processes to selectively kill cancer cells.

MicroRNAs play decisive roles in a variety of diseases, including cancer. This study shows for the first time how mda-7/IL-24 influences an enzyme critical to microRNA processing, and it provides exciting clues as to how this process could be targeted therapeutically,” says Fisher.

The researchers showed that mda-7/IL-24 reduces the expression of an enzyme called DICER, and this effect occurs only in cancer cells. DICER works to process microRNAs for specific cellular functions. In experiments involving prostate, breast and brain cancer cell lines and mouse models, overexpression of DICER was shown to rescue cancer cells from mda-7/IL-24-mediated cell death.

Microphthalmia-associated transcription factor (MITF) was found to be a key mediator in this process. MITF regulates cellular responses to reactive oxygen species (ROS), a natural byproduct of the normal metabolism of oxygen and an important component in cell signaling. In times of cellular stress, ROS levels can increase dramatically and contribute to the development of disease. The scientists showed for the first time that mda-7/IL-24 down-regulates MITF, which, in turn, down-regulates DICER, the target of MITF.

Previous experiments showed a potent bystander effect where mda-7/IL-24 not only killed cancer cells at the primary tumour site but also in distant secondary tumours not directly targeted by the therapy. The bystander effect is mediated, at least in part, by the potent immune activating and anti-growth properties of mda-7/IL-24. These findings help explain why this bystander effect occurs.

“This is an exciting and previously unknown link between mda-7/IL-24 and ROS/MITF/DICER that we plan to continue exploring,” says Fisher. “This research may open up new therapeutic targets, and monitoring the levels of these components could provide important biomarkers to help inform the effectiveness of mda-7/IL-24-based therapies.”

coronary

In patients with acute coronary syndromes, coronary artery stenting, or a history of prior heart attacks, antiplatelet therapy can be lifesaving. Ticagrelor, in combination with aspirin, is commonly prescribed for patients to help prevent blood clotting and subsequent cardiovascular events. But ticagrelor increases these patients’ bleeding risk, and its effects linger even several days after a patient stops taking the medication. This is an important concern for patients who are at risk for major bleeding, such as intracranial or gastrointestinal hemorrhage, and for patients who may need urgent or emergency surgery. Currently, no fast-acting agent is available to reverse the effects of ticagrelor.

In a randomised, double-blind, placebo-controlled, Phase I study of healthy volunteers, a group led by Dr Deepak L. Bhatt, Executive Director of Interventional Cardiovascular Programs at the Brigham and professor of medicine at Harvard Medical School, reported promising results on a potential reversal agent. Dr Bhatt and his colleagues’ findings suggest that this agent, known as PB2452, provides immediate and sustained reversal of ticagrelor’s effects. 

“Ticagrelor is a very effective agent and recommended as a first-line therapy, but if a patient experiences severe bleeding or needs an urgent or emergent procedure, we face a major challenge,” said Dr Bhatt, the lead author of this work. “Having a reversal agent that could quickly and effectively work would represent an important advancement for the field.”

PB2452, developed by the study’s sponsor, PhaseBio Pharmaceuticals, Inc., is a monoclonal antibody fragment that binds ticagrelor with high affinity. In the study, 64 healthy volunteers between 18 and 50 years of age who had been pretreated with ticagrelor received various doses of intravenous PB2452 or a placebo. The team evaluated the effectiveness of PB2452 by analysing platelet function using several methodologies.

Of the 48 volunteers pretreated with ticagrelor, platelet aggregation was suppressed by about 80 percent. After PB2452 administration, ticagrelor’s suppression of platelet aggregation was reversed within five minutes and was sustained for over 20 hours.

There were no serious adverse events or infusion reactions associated with PB2452. There was a total of 30 treatment-emergent adverse events (27 among those who received PB2452 and three among those who received placebo) that were mainly limited to infusion site issues. The team notes some limitations to the study, including that participants were healthy volunteers, not patients with atherosclerosis, and that the sample size was relatively small.

The results were presented at a Featured Clinical Research session at the American College of Cardiology’s 68th Annual Scientific Session and simultaneously published in The New England Journal of Medicine.

cancer-cells

Researchers have discovered a new clue in explaining how cancer cells with identical genomes can respond differently to the same therapy. In a Nature Communications paper published on 21st March 2019, researchers reveal for the first time that the number of mitochondria in a cell is, in great part, associated with how the cancer responds to drug therapy.

Cancer is the second-leading cause of mortality worldwide, with approximately one in six deaths across the globe attributed to the disease. While treatments for cancer continue to improve as technology advances, researchers and clinicians have been unsuccessful in explaining the diversity of responses in cancer cells to treatments of oncological disease.

In many cases, cancer cells with matching genetic makeup will respond differently to the same treatment. Mount Sinai and IBM researchers combined computational and biological methods to uncover a clue to this behaviour.

Cells die when met with bacteria, malnourishment, or viruses. Our bodies also eliminate billions of cells each day – a process known as “programmed cell death” or apoptosis – to promote normal function. Mitochondria, often referred to as the powerhouse of the cell because of their ability to produce cellular energy, can also act as a catalyst in the activation of programmed cell death, and certain anti-cancer drugs work by activating this process.

This function encouraged researchers to explore the hypothesis that cancer cells with identical genetic makeup, but different quantities of mitochondria, may have varying susceptibility to death if exposed to the same drugs that promote apoptosis.

In exposing various types of cells to six concentrations of a pro-apoptotic drug and measuring the abundance of mitochondria within the surviving cells, the researchers discovered that surviving cells had a greater amount of mitochondria than untreated cells. This strongly suggests that cells with fewer mitochondria are more likely to respond to certain drug treatments.

To analyse this data, researchers used a mathematical framework called DEPICTIVE (an acronym for DEtermining Parameter Influence on Cell-to-cell variability Through the Inference of Variance Explained) to quantify variability in the survival or death of cells due to mitochondrial abundance. Overall, the framework determined that the variability of mitochondria explained up to 30 percent of the varying responses to the pro-apoptotic drug.

“Enhancing our understanding of the relationship between mitochondria variability and drug response may lead to more effective targeted cancer treatments, allowing us to find new ways to tackle the problem of drug resistance,” said Pablo Meyer, PhD, Adjunct Assistant Professor of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, Team Leader of Translational Systems Biology at IBM Research, and co-corresponding author of the publication. “The outcomes of this study were truly multidisciplinary, and only made possible by the strong scientific collaboration established between Mount Sinai and IBM.”

COPD

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the US, with approximately 16 million Americans currently affected. 

Researchers at the University of Michigan have reported on the ability of Parametric Response Mapping (PRM), a relatively new technique, to identify small airway abnormality in COPD.

Currently, it is difficult to identify abnormalities in small airways non-invasively, as the tiny bronchioles that are initially damaged are around two millimetres in internal diameter, and as such are too small to be imaged using computed tomography. 

PRM was developed at Michigan Medicine, in a study led by Dr Brian Ross, Professor of Radiology and Biological Chemistry, and Dr Craig Galban, Associate Professor of Radiology. The technique measures lung density during inhalation and exhalation. 

Using lung tissue from patients undergoing transplantation, and donated healthy lung tissue, researchers mapped the samples back to CT scans taken before surgery. The team was able to non-invasively identify small airway loss, narrowing and obstruction.

Senior author Dr MeiLan Han, a lung specialist and Professor of Internal Medicine at the University of Michigan, said, “Now we have confidence in our ability to identify airway disease when imaging COPD patients. PRM is already clinically available and used by University of Michigan clinical teams to assess patients with COPD. This is what we mean by bench to bedside medicine.”

The study was conducted in patients with a severe form of the disease. A NHLBI funded study, COPDGene, found that the PRM-defined small airway abnormalities have been detected on CT scans of patients with milder disease and could help to predict patients who will lose lung function.

Prof Han said, “We still need to validate the type of airway disease the PRM technique identifies in patients with milder disease. That type of lung tissue is more difficult to obtain, but we are working on techniques that would allow us to use smaller amounts of lung tissue to make such studies feasible.” 

The study was published in the American Journal of Respiratory and Critical Care Medicine.

niclosamide

Drug repurposing can often reduce the time and cost it takes to discover and develop a new drug, especially for novel antimicrobial therapies.

Helicobacter pylori is a Gram-negative, helically shaped, stomach pathogen associated with human gastric mucosa. After entering the body, they can cause chronic gastritis, peptic ulcers and gastric carcinoma.

Gastric cancer is developed by around 2.9 percent of people affected by H. pylori, and with some studies suggesting a link between the pathogen and colorectal cancer, it is important that an effective treatment is found.

Researchers in the Infectious Diseases Division at the Warren Alpert Medical School of Brown University, conducted a pilot screening using a broth micro-dilution assay they developed through a previous high-throughput screening method. 

The team found that anthelmintics, such as niclosamide, oxyclozanide, rafoxanide, and closantel, inhibited the growth of the pathogen strain 60190. 

The use of multiple antimicrobial agents can decrease bacterial resistance and re-establish the clinical efficacy of certain antibiotics. Describing how this can occur, the researchers mentioned how the compounds have an inhibitory role on adhesion, with niclosamide inhibiting the secretion of IL-8, despite acidic conditions where it remained stable.

Dr Nagendran Tharmalingam was the first author of the study.

The team used a number of methods in their analyses, including scanning electron microscopic observations, light microscopy, cytotoxicity testing and in vivo efficacy. Antibacterial susceptibility, kinetic, adhesion and invasion, motility and gene expression assays were also conducted, with researchers also investigating the emergence of resistance and membrane potentials.

Using a Two-way ANOVA, followed by a Bonfererroni post-test, the team carried out statistical analyses of their data.

The research team found that niclosamide administration decreased transmembrane pH, indicating that that anti-pathogen activity was related to the disruption of its proton motive force. Niclosamide was effective in infection models, and could be developed further to fight infection by the pathogen. 

Results should be confirmed using more strains of the pathogen.

The study was published in the journal Scientific Reports.

tumour

University of Otago scientists have discovered a way to view the immune cell ‘landscape’ of bowel cancer tumours, paving the way towards more individualised medicine and treatment for many other diseases in future.

The scientists have shown the incredible diversity of immune cells that are inside a colorectal tumour. Immune cells are known to protect against cancer growth and this work provides new information on the types of cells present and how they might be beneficial for the patient.

Lead researcher Associate Professor Roslyn Kemp explained they are using a new technology called high-dimensional mass cytometry to identify cells in the tumours of people with bowel cancer.

“It can be thought of as taking a higher resolution ‘photo’ of the inside of the tumour. The photo may reveal new types of cells that may or may not be targetable by drugs, or reveal different composition of immune cell populations in individuals that could be used to predict the course of the disease.”

Associate Professor Kemp said results of their study have shown there is huge diversity in the type of immune cells that infiltrate the tumour, which means that any one, or more likely a combination of many immune cells, could have an effect on patient outcomes.

She mentioned how the technique could be used to study a number of different diseases.

“It demonstrates the use of a new technology to study the immune response in much more detail than other methods currently used, providing new types of information for patients,” Professor Kemp explained.

“It is a step towards personalised medicine, sometimes referred to as precision medicine, since each patient’s tumour could be looked at with this amount of detail.”

The next step is to carry out a similar study with a slightly different technique to further investigate where all the cells are in the tumour and how that might affect cell function and relationships between types of cells and patient data like stage of disease and patient survival.

The paper was recently published in the Journal of Immunology.