GENE RESPONSIBLE FOR TRAITS INVOLVED IN DIABETES DISCOVERED

A collaborative research team led by Medical College of Wisconsin (MCW) scientists has identified a new gene associated with fasting glucose and insulin levels in rats, mice and in humans. The findings are published in the September issue of Genetics.

Leah Solberg Woods, Ph.D., associate professor of pediatrics at MCW and a researcher in the Children's Hospital of Wisconsin Research Institute, led the study and is the corresponding author of the paper.

The authors of the paper identified a gene called Tpcn2 in which a variant was associated with fasting glucose levels in a rat model. Studies in Tpcn2 knockout mice also demonstrated the difference in fasting glucose levels as well as insulin response between the knockout animals and regular mice. Finally, Dr. Woods' team identified variants within Tpcn2 associated with fasting insulin in humans. Tpcn2 is a lysosomal calcium channel that likely plays a role in insulin signaling. Glucose tolerance, insulin resistance and beta cell dysfunction are key underlying causes of type 2 diabetes.

"Genome-wide association studies in humans have identified 60+ genes linked to type 2 diabetes; however, these genes explain only a small portion of heritability in diabetes studies. As we continue to identify genes and variants of interest, we will evaluate them in multiple models to understand the mechanism of disease," said Dr. Solberg Woods.

According to the American Diabetes Association, 29 million Americans have diabetes -- more than nine percent of the total population. It is the 7th leading cause of death, and experts estimate diabetes is an underreported cause of death because of the comorbidities and complications associated with the disease.

BABIES INTEREST IN FACES LINKED TO CALLOUS EMOTIONAL TRAITS

Scientists at King's College London, the University of Manchester, and the University of Liverpool have found that an infant's preference for a person's face, rather than an object, is associated with lower levels of callous and unemotional behaviors in toddlerhood.

The study, published in Biological Psychiatry, assessed if 213 five-week-old infants spent longer tracking a person's face compared to an inanimate object -- in this case a red ball. The researchers showed that greater tracking of the face relative to the ball was linked to lower callous unemotional behaviors measured using questionnaires when children were two and a half years old. The study also showed that if a mother responds more sensitively to their baby during playtime, then the child is less likely to display callous unemotional behavior as a toddler.

Callous and unemotional behaviors include a lack of guilt and empathy, reduced concern for other's distress and difficulties with understanding emotions. In older children and adults, callous unemotional traits have been associated with reduced attention to important social features such as other people's faces and eyes. This study is the first to examine whether such a relationship is present from the first few weeks of life.

This is the latest finding from the Medical Research Council (MRC) funded Wirral Child Health and Development Study, an ongoing interdisciplinary investigation into the interplay of social and biological factors in the emotional and cognitive development of children. The children are currently being followed to test whether face preference in infancy can predict callous unemotional behavior through to middle childhood.

Dr Rachael Bedford, a Sir Henry Wellcome Postdoctoral Fellow at the Biostatistics Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, says: "Callous and unemotional behaviors in children are known to be associated with an increased emotional burden on families as well as later criminality and antisocial behavior. This study takes us a step further in understanding the earliest origins of callous and unemotional behaviors. An important next step will be to seek replication of the findings before working towards developing early interventions."

Dr Jonathan Hill, University of Manchester, says: "While our findings are interesting, we don't yet know how stable callous unemotional behaviors are. Our follow-up work will assess how these early indicators affect children in later life."

PARTICULAR BRAIN CONNECTIONS LINKED TO POSITIVE HUMAN TRAITS

There is a strong correspondence between a particular set of connections in the brain and positive lifestyle and behaviour traits, according to a new study by Oxford University researchers.

A team of scientists led by the University's Centre for Functional MRI of the Brain has investigated the connections in the brains of 461 people and compared them with 280 different behavioural and demographic measures that were recorded for the same participants. They found that variation in brain connectivity and an individual's traits lay on a single axis -- where those with classically positive lifestyles and behaviours had different connections to those with classically negative ones. The findings are published in Nature Neuroscience.

The team used data from the Human Connectome Project (HCP), a $30m NIH-funded brain imaging study led by Washington, Minnesota and Oxford Universities. The HCP is pairing up functional MRI scans of 1,200 healthy participants with in-depth data gained from tests and questionnaires. "The quality of the imaging data is really unprecedented," explains Professor Stephen Smith, who was the lead author of the paper. "Not only is the number of subjects we get to study large, but the spatial and temporal resolution of the fMRI data is way ahead of previous large datasets." So far, data for 500 subjects have been released to researchers for analysis.

The Oxford team took the data from 461 of the scans and used it to create an averaged map of the brain's processes across the participants. "You can think of it as a population-average map of 200 regions across the brain that are functionally distinct from each other," explains Professor Smith. "Then, we looked at how much all of those regions communicated with each other, in every participant."

The result is a connectome for every subject: a detailed description of how much those 200 separate brain regions communicate with each other, which can be thought of as a map of the brain's strongest connections. The team then added the 280 different behavioural and demographic measures for each subject and performed a 'canonical correlation analysis' between the two data sets -- a mathematical process that can unearth relationships between the two large sets of complex variables.

They found one strong correlation that relates specific variations in a subject's connectome with their behavioural and demographic measures. Interestingly, the correlation shows that those with a connectome at one end of scale score highly on measures typically deemed to be positive, such as vocabulary, memory, life satisfaction, income and years of education. Meanwhile, those at the other end of the scale were found to exhibit high scores for traits typically considered negative, such as anger, rule-breaking, substance use and poor sleep quality.

The researchers point out that their results resemble what psychologists refer to as the 'general intelligence g-factor': a variable first proposed in 1904 that's sometimes used to summarize a person's abilities at different cognitive tasks. While the new results include many real-life measures not included in the g-factor -- such as income and life satisfaction, for instance -- those such as memory, pattern recognition and reading ability are strongly mirrored.

Proponents of the g-factor point out that many intelligence-related measures are inter-related -- suggesting that if you're good at one thing, you're likely to be good at the others, too. However, in the past, the g-factor has also received some criticism, partly because it is not necessarily clear if these correlations between different cognitive abilities are truly reflecting correlations between distinct underlying brain circuits. The new results, however, may provide an opportunity to understand if that's correct, or if the processes in the brain tell a more complex story.

"It may be that with hundreds of different brain circuits, the tests that are used to measure cognitive ability actually make use of different sets of overlapping circuits," explains Professor Smith. "We hope that by looking at brain imaging data we'll be able to relate connections in the brain to the specific measures, and work out what these kinds of test actually require the brain to do."

The team will continue to pursue this investigation as the set of Human Connectome Project data sets made available to researchers increases.