For as long as humans have lived in complex communities, cities and civilizations, they have divided and classified their societies. Those divisions have been based on age, gender, appearance or – in many cases – occupation. In many traditional societies artisans would share the same social status; as would soldiers, priests and workers in any number of other occupations.

In antiquity, the status of a family rarely changed. If you were a farmer, your sons would be farmers, and so on. While today social status barriers are crumbling in many societies, in others they remain largely unchanged.

India’s complex social stratification, known as the caste system, has been one of the traditional cornerstones of society. Though urban Indians are shedding the caste labels of their parents and grandparents, many rural Indians – who make up 72% of the entire population – hold steadfast to the system. In small villages and towns, the Brahmin caste – consisting of scholars and priests – is still revered as one of the highest social strata. And members of the Dalit caste – formerly known as “Untouchables” – are still viewed as unclean and remain separated from others.

The rigidity of the system still present in rural India has made many wonder exactly how long castes have existed. Historical records are unclear, as early Hindu scriptures like the Bhagavad Gita are somewhat ambiguous when it comes to the topic. Some historians even propose that the caste system as we know it today is largely a construct of the English Colonial Era, arguing that the development of such a system could have been deemed necessary to instill order.

Genetic analysis has also proven inconclusive, as analysis of small segments of the human genome has yielded different results. But a new study by geneticist David Reich and colleagues, published in the September 24 issue of Nature, takes a new approach to understanding the genetic history of India.

The core difference between Reich’s genetic analysis and previous studies is in the sheer amount of genetic material analyzed. Reich’s team examined more than 550,000 points across all segments of the human genome. In doing so, they hoped to obtain a more complete picture of Indian genetic history.

The research team analyzed the DNA of 132 individuals from India and neighboring regions, dividing them into 25 distinct groups based on geography, caste and language. They calculated how genetically ‘closed’ each of these groups were. In the caste system it is rare to marry someone from another class, making caste societies very closed, or ‘endogamous.’ If this endogamy continues over many generations, it will leave a behind a genetic signature for scientists to discover.

Reich and his team found such a signature, indicating a long history of endogamy in several of the groups. In fact, the research team calculated that the DNA of six of the groups can be traced back to just a few individuals who lived anywhere from 30 to more than 100 generations ago. Assuming a generation time of 25 years, that establishes the existence of the caste system in the range of 750 to more than 2,500 years ago — long before the British colonial era.

In a second analysis, Reich and his team examined how ancient migrations could have influenced the formation of castes. First the researchers divided the Indian groups into language families: Indo-European and Dravidian. Dravidian tongues, like Tamil and Malayalam, are mainly spoken in southern India and are believed to be a remnant of languages spoken by some of the earliest inhabitants of the region. Indo-European languages, like Punjabi and Urdu, are more common in the north. They are believed to have arrived with a migration of farmers from southwestern Asia or the Near East about 9,000 years ago.

Reich and his colleagues then compared the genetics of each of the Dravidian and Indo-European groups to a sample of European DNA. The team reasoned that, if Indo-European groups were really descended from the farmers, they would show more genetic similarity to the Europeans than the Dravidians.

Not surprisingly, the authors’ hypothesis held true. The Indo-European speakers, like the Kashmiri Pandit and Vaish, were more genetically similar to Europeans. And because the majority of the upper castes speak Indo-European languages, while the lower ones tend to be Dravidian speakers, there could be a relationship between the arrival of Indo-European people and the formation of caste structure. Further evidence that an ancient caste system has permeated through India for thousands of years.

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Unlike the flu virus, which the body is generally able to fight off completely, infection with hepatitis C is often chronic.  That means for most of the three to four million people worldwide who are newly infected each year the virus will persist in the body, where it greatly increases risk for chronic liver diseases including cirrhosis and cancer. The only treatment currently available — an almost year long course of drugs — often causes severe side-effects. Worse yet, it fails in about half of all patients.

Last month, a study published online in the journal Nature showed that DNA variations in and around the IL28B gene influence whether a person chronically infected with the hepatitis C virus will fully respond to the standard treatment regimen. Now three new reports further support the importance of IL28B variations in the body’s response to hepatitis C, a finding that has implications for the future of hepatitis treatment and drug development.

An Australian group headed up by Vijayaprakash Suppiah analyzed the DNA of more than 800 people with European ancestry from Australia, the UK, Germany and Italy infected with hepatitis C.  They found that having one or two copies of the less-common G version of rs8099917, a SNP near the IL28B gene, doubled the odds that a person would fail to have a sustained response to treatment.

A group headed up by Yasuhito Tanaka studied 326 Japanese hepatitis C patients and also found that rs8099917 predicts whether or not a person will respond to treatment.  In this population, however, the effect was much greater.  Carrying a G increased the odds of treatment failure by at least twelve times.

“This SNP has such a strong association with response that, in combination with other parameters, genotyping it and other genetic variants should be a useful part of  clinical management,” write Suppiah et al., who along with Tanaka et al. published their results online this week in the journal Nature Genetics.

Another study, this one published online in Nature, found that variation near IL28B might be part of what allows a minority of people infected with hepatitis C to clear the virus naturally, without any treatment.

David Thomas and colleagues found that individuals with European or African ancestry were about three times more likely to spontaneously clear a hepatitis C infection if they carried two copies of the C version of rs12979860 than if they had CT or TT at this SNP.

Twenty-eight percent of the people with the CT or TT genotypes were able to fight off their hepatitis C infection without treatment, a number very close to the population average.  But 53% of those with the CC genotype were able to become naturally virus-free.

In a commentary published in Nature, Shawn Iadonato and Michael Katze express doubts about the importance of these new discoveries.

“Although these findings raise the tantalizing prospect of a more personalized approach to treating [hepatitis C] by tailoring treatment to patients who are most likely to benefit, the reality is more sobering,” they write.

Iadonato and Katze worry that testing for IL28B variations would not provide doctors with a straightforward yes-or-no answer to the question of whether a patient will respond to hepatitis C treatment.  This is because not all carriers of the advantageous versions of the variants clear the virus, nor do all patients lacking them fail to benefit from treatment.  Furthermore, they point out, there is currently no alternative hepatitis C treatment available.

What they do not consider, however, is how this new research may help change that. In a separate commentary in Nature Genetics, Thomas O’Brien suggests that the current findings could increase the interest in developing hepatitis therapies based on the protein encoded by IL28B, interferon-λ3.  He notes that an early clinical trial testing the effects of a related protein, interferon-λ1, has already had some success.  And certain properties of interferon-λs may cause them to have fewer side effects than current treatments.

O’Brien is still cautious about the findings linking IL28B variations to hepatitis C treatment response.  He says that more research in this area is needed in diverse populations and in people infected with different forms of hepatitis C.  He also stresses that researchers need to consider how these genetic findings fit in with other factors that affect treatment response, including age and gender.

Overall, however, his view is optimistic.  He concludes: “With these caveats, predictive models of HCV treatment response hold the potential to inform treatment decisions for millions of patients who are infected with HCV.”

(Rs12979860 was also described in the original paper linking IL28B to hepatitis C.  23andMe does not currently provide data for this SNP.  As pointed out in the previous Spittoon post on this topic, rs12980275 is very near to this SNP.  The A version of rs12980275 usually corresponds to the C version of rs12979860.  The other SNP discussed in this post, rs8099917, is located close to both rs12979860 and rs12980275.  23andMe customers can look up their data for rs8099917 using the Browse Raw Data feature.  Keep in mind that because all of these SNPs are so closely linked to each other, they are all probably representing the same effect.  More research will be needed to zero in on the exact variation(s) that are important for hepatitis C.)

SNPwatch gives you the latest news about research linking various traits and conditions to individual genetic variations. These studies are exciting because they offer a glimpse into how genetics may affect our bodies and health; but in most cases, more work is needed before this research can provide information of value to individuals. For that reason it is important to remember that like all information we provide, the studies we describe in SNPwatch are for research and educational purposes only. SNPwatch is not intended to be a substitute for professional medical advice; you should always seek the advice of your physician or other appropriate healthcare professional with any questions you may have regarding diagnosis, cure, treatment or prevention of any disease or other medical condition.

Map: PhilippN

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New genetic research may eventually help doctors identify those people with hepatitis C for whom the standard treatment, a grueling 48 week drug regimen, is doomed to fail.

In close to 1,700 people chronically infected with hepatitis C, researchers from Duke University found that those with two Cs at rs12979860 were more likely to have no detectable virus in their blood than those with TT at this SNP after 48 weeks of treatment with a combination of interferon and ribavirin.

The results, published online yesterday in the journal Nature, show that the virus was eradicated in close to 80% of people with two Cs, compared to only about 25% of those with TT. Treatment response in people with CT at rs12979860 was intermediate between the people with CC and TT.

Previously, one of the best predictors of treatment success has been ethnicity: people with European ancestry tend to respond better than African Americans. In the current study, 56% of European Americans were free of the virus after the treatment and follow-up period, while only about 24% of African Americans were.

The researchers determined that approximately half of this disparity is due to the differences in frequency of the C version of rs12979860 in different populations. Europeans are much more likely to be CC than African Americans. Other researchers have shown that Asians, most of whom are CC, are even more likely to become virus-free after treatment than Europeans.

Even though African Americans with hepatitis C respond poorly to treatment with interferon and ribavirin in general, 53% of those with CC at rs12979860 cleared the virus from their systems after treatment, compared to only 33% of Europeans with TT at this SNP.  As new drugs become available, information like this will be invaluable in determining what is likely to work best for each patient. Physicians will be able to base their prescription decisions on genetics instead of generalizations based on race, and patients will get medicines based on biology, not skin color.

(23andMe does not provide data for rs12979860 at this time.  A nearby SNP that was also significantly associated with hepatitis C treatment response was rs12980275.  Customers can check their data for this SNP using the Browse Raw Data feature. The A version of rs12980275 corresponds to the C version of rs12979860 and a better response to treatment. Because the two SNPs are not perfectly correlated, the magnitude of the effect of rs12980275 may not be the same as reported for rs12979860 and discussed above.)

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It’s no secret that obesity rates are rising — quickly.  Between 2000 and 2005 the prevalence of obesity rose by 24%.  Extreme obesity increased by more than 50%.  If current trends continue, more than half of all Americans will be clinically obese by the year 2030.

Rapid changes in the prevalence of a disorder suggest that environmental rather than genetic factors are to blame. But scientists know from twin and adoption studies that body mass index (BMI) is highly heritable.  So which is it: nature or nurture?

As with many aspects of human health, it’s both.  Some people have the bad luck to have inherited genetic variations that together with the modern environment – sedentary jobs and hobbies, easy access to calorie-dense foods – create the perfect storm for the onset of obesity.

Changing the environmental factors that lead to obesity in some people seems simple enough – more exercise, less food.  But public health campaigns touting these commonsense fixes have had little effect against the obesity epidemic. By understanding the genetic aspects of obesity, and how they interact with the environment, scientists may be able to develop more effective treatments and prevention strategies.

In the July issue of Nature Reviews Genetics Andrew J. Walley of Imperial College London and colleagues review the current state of obesity genetics research.  While much progress has been made, the authors make it clear that there is still a long way to go, as the genes identified thus far explain only a tiny fraction of the total genetic component of obesity.

One key to future advancements in obesity genetics research, say Walley et al., lies in improvements to current genomewide association study (GWAS) methods.

First, the authors recommend that researchers focus on recruiting extremely obese people for their studies to increase the likelihood of finding genes with large effects. They also suggest that scientists should stop using BMI as their primary measurement of obesity.  While simple and cheap, this method does not take fat distribution or the ratio of fat to muscle into account.  There are more sophisticated methods, such as CT scans, MRI scans and ultrasound imaging, as well as machines that use air displacement to measure body volume and weight and can calculate fat and fat-free body mass.  Technological advances that will reduce the costs associated with genotyping, and ultimately genetic sequencing, are also needed so that larger numbers of subjects can be studied.

Beyond these improvements to current GWAS methods, Walley et al. say studies of more than just common variations are needed.  They suggest that investigations of rare SNPs, copy number variations (duplications, insertions and deletions of DNA) and inherited changes that don’t affect the actual DNA sequence will be needed to fully understand the genetics of obesity.

There are several competing theories about the overall biological basis of obesity.  Some suggest that obesity is a disorder of energy balance in the body, while others think regulation of the growth of fat cells is the key.  Still others think obesity may be due to defects in the neurological control of appetite and food intake.  Continued advancements in understanding the genetics of obesity will help scientists tease these theories apart, and hopefully lead to a healthier future.

(23andMe customers can check their data for a SNP in the FTO gene in the Obesity Research Report.  So far, this is the genetic variant most strongly associated with the risk of obesity.  There is also an Obesity Preliminary Research Report.)

Related posts in the Spittoon:

SNPwatch: New Obesity SNPs Point To The Brain’s Role In Regulating Appetite

SNPwatch: Gene Variant Linked To Obesity Affects Food Choices In Children

Genetics May Dull Brain’s Pleasure Response To Food, Causing Weight Gain

SNPwatch: Genetic Variants Affect Weight Loss Drug Effectiveness

SNPwatch: Genetic Link Between Obesity and Colorectal Cancer

It’s Not Genes Or Environment, It’s Genes AND Environment

SNPwatch: Researchers Find Genetic Variants That May Influence Risk For Obesity

SNPwatch: MC4R Gene Associated With Body Mass

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In the 1950s, a child born with cystic fibrosis didn’t have much chance of making it to elementary school.  But now, thanks to a better understanding of the disease and improved treatments, people with cystic fibrosis live well into adulthood.

A person must inherit a mutated copy of the CFTR gene from each parent in order to develop cystic fibrosis.  Hundreds of disease-causing mutations have been documented, and the different mutations and combinations of mutations are known to lead to varying constellations of symptoms and degrees of disease severity.  But even in patients with the same combination of mutations there can be differences in how the disease manifests, suggesting that factors beyond CFTR – either environmental or genetic – are involved.

The results of a new study, published online today by the journal Nature, identify a gene that appears to modulate the severity of obstructive lung disease, the major cause of morbidity and mortality in cystic fibrosis patients.  And paradoxically, although cystic fibrosis lung disease is largely the result of inflammation brought on by repeated bouts of infection, a variation that leads to reduced levels of lung disease seems to make certain immune cells known as neutrophils less effective at fighting infections.

“Neutrophils appear to be particularly bad actors in cystic fibrosis.  They are important to the immune system’s response to bacterial infection.  In cystic fibrosis, however, neutrophilic airway inflammation is dysregulated, eventually destroying the lung,” said the study’s senior author, Dr. Christopher Karp, director of Molecular Immunology at Cincinnati Children’s Hospital Medical Center, in a statement.

The researchers tested the DNA of more than 3,000 people with cystic fibrosis and found that the IFRD1 gene was associated with lung disease severity. Specifically, people having the CT genotype at rs7817 showed worse lung function than people with either two Cs or two Ts at this SNP.

That would suggest a lung function advantage for CF patients with one copy of each version of rs7817. But in laboratory experiments with cells taken from healthy volunteers, a different and more plausible pattern emerged: Each C at rs7817 led to reduced neutrophil activity. This reduced activity may be the link between IFRD1 and lung disease severity in cystic fibrosis patients.

Research in mice supports that view. Mice genetically engineered to lack the IFRD1 gene show less neutrophil activity, further supporting the importance of this gene in controlling the activity of these cells.  When infected with P. aeruginosa, a type of bacteria that often infects the lungs of people with cystic fibrosis, IFRD1-deficient mice were less able to rid their lungs of the bacteria than normal mice.  But, as would be predicted from the results in humans, these mutant mice showed fewer signs of inflammation and were actually healthier than the normal mice.

The researchers reason that variations in IFRD1 that reduce neutrophil activity prevent excess inflammation, and therefore reduce the severity of lung disease. The scientists did not address why patients with two Ts had better, not worse, lung function compared to those with one.

Although they caution that more research will be needed, the authors of the study conclude that, “the current data suggest probable benefit for therapeutic targeting of neutrophils in this devastating disease.  These data also suggest that [IFRD1] may provide a tractable therapeutic target in CF, and other diseases in which neutrophils have an important pathogenetic role.”

(23andMe customers can find out about their data for one of the most common CFTR mutations, Delta F508, in the Carrier Status Clinical Report for cystic fibrosis.  It is important to note that not carrying this mutation does not mean that another mutation is not present.)

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Understanding the genetic changes that lead to different cancers is key to more effective diagnosis and treatment of the disease. And thanks to the availability of faster, cheaper genome sequencing technologies, researchers are now able to peer more deeply into the DNA of cancer cells than ever before.

Recent studies have sequenced more than 600 genes in both brain and lung cancer samples and found novel patterns of gene mutation. But in both of these studies, the findings were limited to genes the researchers already suspected of involvement in cancer.

Now researchers from Washington University in St. Louis have taken an unbiased approach to finding mutated cancer genes and found that half of the ones they identified were completely unexpected. The researchers describe their work in a paper published online today by Nature.

“In the past, cancer researchers have been ‘looking under the lamppost’ to find the causes of malignancy – but now the team from Washington University has lit up the whole street,” said Francis Collins, former director of the National Human Genome Research Institute, in a statement.

Instead of looking at a subset of genes already thought to be involved in cancer, the Washington University researchers cast their net as broadly as possible by sequencing the complete genomes of an acute myeloid leukemia (AML) patient’s normal and tumor cells.

Nearly 2.7 million variations in the DNA of the patient’s tumor were initially flagged, but almost 98% of these were also found in the patient’s normal cells, indicating that these mutations were in her genome from the beginning and not the root of her cancer.

The researchers then used a variety of methods to further narrow down the field of mutations that might be responsible for the patient’s cancer. They were ultimately left with single-base mutations in just eight genes. Half of those eight were in gene families already strongly associated with cancer in general, while the other four occurred in genes not previously implicated in the disease. None of the eight mutations had previously been reported for AML before. Nor could any of them be found in the tumors of an additional 187 AML patients the researchers tested.

“This suggests that there is a tremendous amount of genetic diversity in cancer, even in this one disease,” team leader Richard Wilson said in statement. “There are probably many, many ways to mutate a small number of genes to get the same result, and we’re only looking at the tip of the iceberg in terms of identifying the combinations of genetic mutation that can lead to AML.”

Although the results of this study can’t tell a doctor how to treat better treat a patient, the research is an essential first step down the path towards developing targeted therapies, said Brian Druker, a cancer genetics researcher whose own work helped with the development of the targeted cancer drug Gleevec, in a statement.

“This tour-de-force effort identified a small number of mutations in genes that no one predicted, and their uniqueness for this patient begins to give us a glimmer of the genetic complexity and diversity of this disease,” he said.

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If you take two members of the human race at random and ask how much their genomes differ, you’ll get a surprising answer: they’re almost identical.

On average, for every 1,000 DNA bases you have, 999 or so of them are exactly the same between you and your neighbor – and for that matter, between you and your neighbors on the other side of the planet. Over your entire 6 billion DNA base pair genome, however, that one difference in a thousand adds up to several millions of differences.

In studies published by Science and Nature this week, scientists have taken their most detailed look yet at these genetic differences. In this blog post, we’ll take a brisk stroll through their findings.

Both studies are based on around 600,000 SNPs genotyped in individuals (i.e., people) from the Human Genome Diversity Panel(HGDP-CEPH). HGDP-CEPH is a remarkable scientific resource. It consists of immortalized cell lines from 1064 individuals in 51 populations scattered around the globe. The idea guiding the creation of the panel was to take a wide-angle snapshot of human genetic diversity. This explains the presence in the panel of little-known populations like the Uygur, the Surui, and the Xibo, alongside more familiar populations like the Japanese, Palestinians, and French. This polyglot collection reposes at the Fondation Jean Dausset in Paris, as it has now for nearly a decade.

The Science study peers closely into those one-per-thousand differences between people, asking: Of all the genetic diversity seen in the panel, how much is found between people from the same population, how much between people from different populations in the same geographic region, and how much between people from different geographic regions?

For example, if there were no within-population diversity that would mean that all Russians are genetically identical, all Surui are identical, and so on, and therefore that all human genetic diversity must exist at the population and regional levels.

The paper finds nearly the opposite. About 90% of human diversity exists within populations, with most of the remaining 10% existing between geographic regions. This strongly confirms a decades-old result in human genetics: of those very few DNA bases which differ between people, a small minority of these differ between peoples.

Even so, 10% of several million differences is still a lot of differences between populations. Both studies zoom in on these differences, mustering some mathematical machinery called Bayesian cluster analysis, and ask: how easy is it to guess someone’s ethnicity based on their genotype? The answer the two papers find is that it’s pretty easy, at least on the regional scale. The following figure, drawn from earlier work done by many of the same researchers that was published in the open-access journal PLoS Genetics in 2005, illustrates the results of the analysis; these are qualitatively the same as the results shown in the fancifully-priced Science and Nature figures.

Each one of the (very) thin vertical lines in the figure represents a person, and the colors comprising each line correspond to the inferred proportion of ancestry from each of seven world regions. The key here is that the cluster analysis has no notion of a region or a population. It is simply told to divide up the genetic diversity into seven clusters (or six or eight – the results don’t change much), and then to guess which cluster or clusters each individual belongs to. The ethnic and regional labels are only applied once the analysis is through and, as is plain, the agreement between the donor-supplied ethnic label and the assignment is quite strong.

The papers go much further than we’ve seen here, looking into the history of human migration and exploring what happens when you use DNA insertions and deletions instead of SNPs to ask the same questions.

It’s worth noting that 23andMe is proud to have cosponsored the genotyping of the HGDP-CEPH that was conducted by the authors of the Science paper. The genotypes are available, gratis, at the CEPH website. We downloaded them ourselves, and now our customers can compare themselves to these very same populations using our Global Similarity feature.

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23andMe was founded in part to harness the natural curiosity that results when people can see how new knowledge applies to them personally. When new customers join 23andMe they are not just getting access to their genomes and the scientific knowledge that gives it meaning – they are also contributing their genetic information to our research database. The hope of 23andMe is that they will be willing to take the next step and contribute additional information to enable the creation of even more knowledge.

As the Nature Genetics editors observed, “it would be wrong to underestimate the motivational potential inherent in handing people their genomes and asking them to participate in finding out more … ”

Once our database is large enough, we plan to ask our customers to provide additional information beyond their genetic data – it could be anything from symptoms of autism to shoe size. That information would be used in research that could discover even more genetic links to traits and diseases.

Participation in these follow-on studies will be voluntary, but we believe that our customers’ curiosity and generosity will motivate them to take part. Our customers may even want to propose and help organize their own studies.

The beauty of this arrangement is that every discovery our customers contribute to has the potential to make their own data that much more meaningful and valuable, and we think it could lead to rapid advancement in understanding of the human genome in general. We envision a virtuous circle of inquiry and discovery, as our customers repeatedly lend their data for research and reap the benefits of the new knowledge it produces, whether directly or indirectly.

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