A genetic ‘switch’ has been discovered by MRC researchers at the University of Leicester that could help to prevent or delay the symptoms of Parkinson’s disease.

In a paper, the team discovered that a gene called ATF4 plays a key role in Parkinson’s disease, acting as a ‘switch’ for genes that control mitochondrial metabolism for neuron health.

Dr Miguel Martins from the MRC Toxicology Unit at the University of Leicester, who led the research, explained: “When the expression of ATF4 is reduced in flies, expression of these mitochondrial genes drops. This drop results in dramatic locomotor defects, decreased lifespan, and dysfunctional mitochondria in the brain.

“Interestingly, when we overexpressed these mitochondrial genes in fly models of Parkinson’s, mitochondrial function was re-established, and neuron loss was avoided.”

By discovering the gene networks that orchestrate this process, the researchers have singled out new therapeutic targets that could prevent neuron loss.

Some forms of Parkinson’s are caused by mutations in the genes PINK1 and PARKIN, which are instrumental in mitochondrial quality control.

Fruit flies with mutations in these genes accumulate defective mitochondria and exhibit Parkinson’s-like changes, including loss of neurons.

The researchers used PINK1 and PARKIN mutant flies to search for other critical Parkinson’s genes – and using a bioinformatics approach discovered that the ATF4 gene plays a key role.

Dr Martins added: “Studying the roles of these genes in human neurons could lead to tailored interventions that could one day prevent or delay the neuronal loss seen in Parkinson’s.”

The findings build upon recent research by the University of Leicester team, which recently discovered several genes that protect neurons in Parkinson’s disease, creating possibilities for new treatment options.

University of Leicester www2.le.ac.uk/offices/press/press-releases/2017/february/discovery-of-genetic-2018switch2019-could-help-to-prevent-symptoms-of-parkinson2019s-disease

Researchers investigating a form of adult-onset diabetes that shares features with the two better-known types of diabetes have discovered genetic influences that may offer clues to more accurate diagnosis and treatment.

Latent autoimmune diabetes in adults (LADA) is informally called "type 1.5 diabetes" because like type 1 diabetes (T1D), LADA is marked by circulating autoantibodies, an indicator that an overactive immune system is damaging the body’s insulin-producing beta cells. But LADA also shares clinical features with type 2 diabetes (T2D), which tends to appear in adulthood. Also, as in T2D, LADA patients do not require insulin treatments when first diagnosed.

A study uses genetic analysis to show that LADA is closer to T1D than to T2D. "Correctly diagnosing subtypes of diabetes is important, because it affects how physicians manage a patient’s disease," said co-study leader Struan F.A. Grant, PhD, a genomics researcher at Children’s Hospital of Philadelphia (CHOP). "If patients are misdiagnosed with the wrong type of diabetes, they may not receive the most effective medication."

Grant collaborated with European scientists, led by Richard David Leslie of the University of London, U.K.; and Bernhard O. Boehm, of Ulm University Medical Center, Germany and the Lee Kong Chian School of Medicine, a joint medical school of Imperial College London and Nanyang Technological University, Singapore.

Occurring when patients cannot produce their own insulin or are unable to properly process the insulin they do produce, diabetes is usually classified into two major types. T1D, formerly called juvenile diabetes, generally presents in childhood, but may also appear first in adults. T2D, formerly called non-insulin-dependent diabetes, typically appears in adults, but has been increasing over the past several decades in children and teens. Some 90 percent or more of all patients with diabetes are diagnosed with T2D.

Grant and many other researchers have discovered dozens of genetic regions that increase diabetes risk, usually with different sets of variants associated with T1D compared to T2D. The current study, the largest-ever genetic study of LADA, sought to determine how established T1D- or T2D-associated variants operate in the context of LADA.

The study team compared DNA from 978 LADA patients, all adults from the U.K. and Germany, to a control group of 1,057 children without diabetes. Another set of control samples came from 2,820 healthy adults in the U.K. All samples were from individuals of European ancestry.

The researchers calculated genetic risk scores to measure whether LADA patients had genetic profiles more similar to those of T1D or T2D patients. They found several T1D genetic regions associated with LADA, while relatively few T2D gene regions added to the risk of LADA. The genetic risk in LADA from T1D risk alleles was lower than in childhood-onset T1D, possibly accounting for the fact that LADA appears later in life.

One variant, located in TCF7L2, which Grant and colleagues showed in 2006 to be among the strongest genetic risk factors for T2D reported to date, had no role in LADA. "Our finding that LADA is genetically closer to T1D than to T2D suggests that some proportion of patients diagnosed as adults with type 2 diabetes may actually have late-onset type 1 diabetes," said Grant.

Grant said that larger studies are needed to further uncover genetic influences in the complex biology of diabetes, adding, "As we continue to integrate genetic findings with clinical characteristics, we may be able to more accurately classify diabetes subtypes to match patients with more effective treatments."

EurekAlertwww.eurekalert.org/pub_releases/2017-05/chop-gfi050417.php

An enzyme found in the fluid around the brain and spine is giving researchers a snapshot of what happens inside the minds of Alzheimer’s patients and how that relates to cognitive decline.

Iowa State University researchers say higher levels of the enzyme, autotaxin, significantly predict memory impairment and Type 2 diabetes. Just a one-point difference in autotaxin levels – for example, going from a level of two to a three – is equal to a 3.5 to 5 times increase in the odds of being diagnosed with some form of memory loss, said Auriel Willette, an assistant professor of food science and human nutrition at Iowa State.

Autotaxin, often studied in cancer research, is an even stronger indicator of Type 2 diabetes. A single point increase reflects a 300 percent greater likelihood of having the disease or pre-diabetes. Willette and Kelsey McLimans, a graduate research assistant, say the discovery is important because of autotaxin’s proximity to the brain.

“We’ve been looking for metabolic biomarkers which are closer to the brain. We’re also looking for markers that reliably scale up with the disease and have consistently higher levels across the Alzheimer’s spectrum,” Willette said. “This is as directly inside of the brain as we can get without taking a tissue biopsy.”

Willette’s previous research found a strong association between insulin resistance and memory decline and detrimental brain outcomes, increasing the risk for Alzheimer’s disease. Insulin resistance is a good indicator, but Willette says it has limitations because what happens in the body does not consistently translate to what happens in the brain. That is why the correlation with this new enzyme found in the cerebrospinal fluid is so important.

“It has a higher predictive rate for having Alzheimer’s disease,” McLimans said. “We also found correlations with worse memory function, brain volume loss and the brain using less blood sugar, which have also been shown with insulin resistance, but autotaxin has a higher predictive value.”

The fact that autotaxin is a strong predictor of Type 2 diabetes and memory decline emphasizes the importance of good physical health. Researchers say people with higher levels of autotaxin are more likely to be obese, which often causes an increase in insulin resistance.

Willette says autotaxin levels can determine the amount of energy the brain is using in areas affected by Alzheimer’s disease. People with higher autotaxin levels had fewer and smaller brain cells in the frontal and temporal lobes, areas of the brain associated with memory and executive function. As a result, they had lower scores for memory and tests related to reasoning and multitasking.

“Autotaxin is related to less real estate in the brain, and smaller brain regions in Alzheimer’s disease mean they are less able to carry out their functions,” Willette said. “It’s the same thing with blood sugar. If the brain is using less blood sugar, neurons have less fuel and start making mistakes and in general do not process information as quickly.”

Iowa State University www.news.iastate.edu/news/2016/12/19/alzheimersautotaxin

An algorithm based on levels of metabolites found in a blood sample can accurately predict whether a child is on the Autism spectrum of disorder (ASD), based upon a recent study. The algorithm, developed by researchers at Rensselaer Polytechnic Institute, is the first physiological test for autism and opens the door to earlier diagnosis and potential future development of therapeutics.
 
“Instead of looking at individual metabolites, we investigated patterns of several metabolites and found significant differences between metabolites of children with ASD and those that are neurotypical. These differences allow us to categorize whether an individual is on the Autism spectrum,” said Juergen Hahn, lead author, systems biologist, professor, and head of the Rensselaer Department of Biomedical Engineering. “By measuring 24 metabolites from a blood sample, this algorithm can tell whether or not an individual is on the Autism spectrum, and even to some degree where on the spectrum they land.”
 
Big data techniques applied to biomedical data found different patterns in metabolites relevant to two connected cellular pathways that have been hypothesized to be linked to ASD: the methionine cycle and the transulfuration pathway. The methionine cycle is linked to several cellular functions, including DNA methylation and epigenetics, and the transulfuration pathway results in the production of the antioxidant glutathione, decreasing oxidative stress.
 
Autism Spectrum Disorder is estimated to affect approximately 1.5 percent of individuals and is characterized as “a developmental disability caused by differences in the brain,” according to the Centers for Disease Control and Prevention. The physiological basis for ASD is not known, and genetic and environmental factors are both believed to play a role. People with ASD “may communicate, interact, behave, and learn in ways that are different from most other people.” According to the CDC, the total economic costs per year for children with ASD in the United States are estimated between $11.5 billion and $60.9 billion. Research shows that early intervention can improve development, but diagnosis currently depends on clinical observation of behavior, an obstacle to early diagnosis and treatment. Most children are not diagnosed with ASD until after age 4 years.

Rensselaer Polytechnic Institute
news.rpi.edu/content/2017/03/16/blood-test-autism

The first analysis of nearly 19,000 de-identified genomic records from the American Association for Cancer Research (AACR) international data-sharing initiative known as AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) has been published.
In addition to the genomic analysis, the report includes examples of how the AACR Project GENIE genomic data can be used to facilitate clinical research, including:
Analysis showing that more than 30 percent of the samples had mutations that are clinically actionable, meaning that they are suggestive of a specific treatment that is either already approved by the U.S. Food and Drug Administration or is being tested in clinical trials.
Analysis showing that the rate at which patients with samples in the AACR Project GENIE registry would match with arms of the NCI-MATCH trial reflected the actual accrual rates for the trial.
Details of two additional studies underway that are linking certain genetic characteristics of metastatic breast cancer with clinical and pathological features of the tumors, as well as with patient outcomes.
“There has been a lot of discussion about the potential of data-sharing initiatives to accelerate the pace of progress against cancer,” said Charles L. Sawyers, MD, FAACR, who is the AACR Project GENIE Steering Committee chairperson and an author on the paper. “This paper shows that AACR Project GENIE has made the first steps to delivering on this promise.
“We are particularly excited by the clinical actionability analysis,” continued Sawyers, who is also chairperson of the Human Oncology and Pathogenesis Program at Memorial Sloan Kettering Cancer Center in New York, and a Howard Hughes Medical Institute investigator. “Prior studies looking at how often tumour genome sequencing identifies a clinically actionable mutation have yielded variable results, leading some to question its clinical utility. The huge number of samples in our study and the high rate of clinical actionability give us confidence that tumour genome sequencing can have an important role in clinical care.”
AACR Project GENIE is a multi-phase, multi-year, international data-sharing project that was launched by the AACR in partnership with eight global academic leaders in clinical cancer genomics in November 2015. Just over a year later, in January 2017, the AACR Project GENIE consortium made public nearly 19,000 de-identified genomic records collected from patients who were treated at the eight international institutions participating in the first phase of the project.
“This paper describes the AACR Project GENIE consortium and provides a landscape overview of the first public GENIE data release,” said Ethan Cerami, PhD, director of the Knowledge Systems Group and lead scientist in the Department of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute in Boston, and an author on the paper. “By showing that we can share data across multiple institutions in the United States, Canada, and Europe to obtain results none of the institutions could have obtained alone, we have put AACR Project GENIE at the forefront of data-sharing efforts to accelerate scientific discovery and ultimately improve patient care.”

American Association for Cancer Research
www.aacr.org/Newsroom/Pages/News-Release-Detail.aspx?ItemID=1059#.WTSKEmSGP5Y