Diabetes Genetics Study Brings In Data From Different Ethnic Groups

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February 10, 2014

University of Oxford

Seven new genetic regions associated with type 2 diabetes have been identified in the largest study to date of the genetic basis of the disease.

DNA data was brought together from more than 48,000 patients and 139,000 healthy controls from four different ethnic groups. The research was conducted by an international consortium of investigators from 20 countries on four continents, co-led by investigators from Oxford Universitys Wellcome Trust Centre for Human Genetics.

The majority of such genome-wide association studies have been done in populations with European backgrounds. This research is notable for including DNA data from populations of Asian and Hispanic origin as well.

The researchers believe that, as more genetic data increasingly become available from populations of South Asian ancestry and, particularly, African descent, it will be possible to map genes implicated in type 2 diabetes ever more closely.

One of the striking features of these data is how much of the genetic variation that influences diabetes is shared between major ethnic groups, says Wellcome Trust Senior Investigator Professor Mark McCarthy from the University of Oxford. This has allowed us to combine data from more than 50 studies from across the globe to discover new genetic regions affecting risk of diabetes.

He adds: The overlap in signals between populations of European, Asian and Hispanic origin argues that the risk regions we have found to date do not explain the clear differences in the patterns of diabetes between those groups.

Among the regions identified by the international research team are two, near the genes ARL15 and RREB1, that also show strong links to elevated levels of insulin and glucose in the body two key characteristics of type 2 diabetes. This finding provides insights into the ways basic biochemical processes are involved in the risk of type 2 diabetes, the scientists say.

The genome-wide association study looked at more than 3 million DNA variants to identify those that have a measurable impact on risk of type 2 diabetes. By combining DNA data from many tens of thousands of individuals, the consortium was able to detect, for the first time, regions where the effects on diabetes susceptibility are rather subtle.

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Diabetes Genetics Study Brings In Data From Different Ethnic Groups

New Interactive Map Reveals Human History Of Genetic Mixing

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Lawrence LeBlond for redOrbit.com Your Universe Online

A multi-institutional team of researchers this week published in the journal Science a study identifying, dating and characterizing the genetic mixing between populations around the world. Along with the study, the team released an interactive map detailing the histories of this genetic mixing.

Researchers from Max Planck Institute for Evolutionary Anthropology, Oxford University and University College London developed sophisticated statistical methods to analyze the DNA of nearly 1500 people from 95 different populations around the world and from over the past four millennia. These populations hailed from Europe, Africa, Asia and South and Central America.

The groups work was funded by the Wellcome Trust and Royal Society.

DNA really has the power to tell stories and uncover details of humanitys past, said co-senior study author Dr Simon Myers, of Oxford Universitys Department of Statistics and Wellcome Trust Centre for Human Genetics.

Because our approach uses only genetic data, it provides information independent from other sources. Many of our genetic observations match historical events, and we also see evidence of previously unrecorded genetic mixing. For example, the DNA of the Tu people in modern China suggests that in around 1200CE, Europeans similar to modern Greeks mixed with an otherwise Chinese-like population. Plausibly, the source of this European-like DNA might be merchants travelling the nearby Silk Road, explained Dr Myers in a statement.

Dubbed Globetrotter, this powerful technique provides a good in-depth look at the past. For Instance, the method provided invaluable insight into the genetic legacy of the Mongol Empire. Historically, it is believed that the Hazara people of Pakistan are partially descended from Mongol warriors; the study found clear evidence to back up this belief, discovering that Mongol DNA had in fact entered the Pakistani population during the Mongol Empire. As well, six other neighboring populations showed similar evidence of genetic mixing with the Mongols during this period.

What amazes me most is simply how well our technique works, said study lead author Dr Garrett Hellenthal, of the UCL Genetics Institute. Although individual mutations carry only weak signals about where a person is from, by adding information across the whole genome we can reconstruct these mixing events. Sometimes individuals sampled from nearby regions can have surprisingly different sources of mixing.

For example, we identify distinct events happening at different times among groups sampled within Pakistan, with some inheriting DNA from sub-Saharan Africa, perhaps related to the Arab Slave Trade, others from East Asia, and yet another from ancient Europe. Nearly all our populations show mixing events, so they are very common throughout recent history and often involve people migrating over large distances, said Dr Hellenthal.

The team also identified chunks of DNA shared between individuals from different populations, based on the genome data taken from all 1490 individuals. They found that those populations that shared more ancestry also shared more of these chunks. As well, individual chunks gave the team clues about the underlying ancestry along chromosomes.

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New Interactive Map Reveals Human History Of Genetic Mixing

Genome Editing Goes Hi-Fi

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Sometimes biology is cruel. Sometimes simply a one-letter change in the human genetic code is the difference between health and a deadly disease.

But even though doctors and scientists have long studied the often devastating disorders caused by these tiny changes, replicating these changes in the lab in order to study them in human stem cells has proven challenging. But now, scientists at the UC San Francisco-affiliatedGladstone Institutes have found a way to efficiently edit the human genome one letter at a time not only boosting researchers ability to model human disease, but also paving the way for therapies that cure disease by fixing these so-called bugs in a patients genetic code.

Bruce Conklin, MD

Led by Gladstone investigator and professor in the UCSF School of Medicine,Bruce Conklin, MD, the research team describes in an issue ofNature Methods how they have solved one of science and medicines most pressing problems: how to efficiently and accurately capture rare genetic mutations that cause disease as well as how to fix them. This pioneering technique highlights the type of out-of-the-box thinking that is often critical for scientific success.

Advances in human genetics have led to the discovery of hundreds of genetic changes linked to disease, but until now weve lacked an efficient means of studying them, explained Conklin. To meet this challenge, we must have the capability to engineer the human genome, one letter at a time, with tools that are efficient, robust and accurate. And the method that we outline in our study does just that.

One of the major challenges preventing researchers from efficiently generating and studying these genetic diseases is that they can exist at frequencies as low as one-in-a-thousand, making the task of finding and studying them labor-intensive.

For our method to work, we needed to find a way to efficiently identify a single mutation in a cell among hundreds of normal, healthy cells, explained Gladstone research scientist Yuichiro Miyaoka, PhD, the papers lead author. So we designed a special fluorescent probe that would distinguish the mutated sequence from the original sequences. We were then able to sort through both sets of sequences and detect mutant cells even when they made up as little one in every thousand cells. This is a level of sensitivity more than one hundred times greater than traditional methods.

The team then applied these new methods to induced pluripotent stem cells, or iPS cells. These cells, derived from the skin cells of human patients, have the same genetic makeup including any potential disease-causing mutations as the patient. In this case, the research team first used a highly advanced gene-editing technique called TALENs to introduce a specific mutation into the genome. Some gene-editing techniques, while effective at modifying the genetic code, involve the use of genetic markers that then leave a scar on the newly edited genome. These scars can then affect subsequent generations of cells, complicating future analysis. Although TALENs, and other similarly advanced tools, are able to make a clean, scarless single letter edits, these edits are very rare, so that new technique from the Conklin lab is needed.

Our method provides a novel way to capture and amplify specific mutations that are normally exceedingly rare, saidConklin. Our high-efficiency, high-fidelity method could very well be the basis for the next phase of human genetics research.

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Genome Editing Goes Hi-Fi

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