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Kathryn Paige Harden argues how far we go in formal education and the huge knock-on effects that has on our income, employment and health is in part down to our genes. Harden is a professor of psychology at the University of Texas at Austin, where she leads a lab using genetic methods to study the roots of social inequality. Her provocative new book is The Genetic Lottery: Why DNA Matters for Social Equality.

To even talk about whether there might be a genetic element to educational attainment and social inequality breaks a huge social taboo particularly on the political left, which is where you say your own sympathies lie. The spectre of eugenics looms large, and no one wants to create a honeypot for racists and classists. To be clear, it is scientifically baseless to make any claims about differences between racial groups, including intelligence, and you are not doing that. But why go here?I wrote this book first for my fellow scientists, who havent necessarily seen the relevance of genetics for their own work or have been afraid to incorporate it because of these associations. There is a large body of scientific knowledge being ignored lest the eugenics genie be let out of the bottle.

But also people are hearing every day about new genetic discoveries and seeing in their own families and lives that genetics matter. When asked to estimate how much genes influence intelligence, peoples answers are not zero. Im trying to help them make sense of that information in a socially responsible way. If you care about social equality, what do you do with information about genetics?

You have been accused of promoting eugenics, including by prominent sociologist Ruha Benjamin, who has written that you are engaging in savvy slippage between genetic and environmental factors that would make the founders of eugenics proud.Those fears are coming out of a very real place historically, genetics has been misused. But [eugenics] is literally the opposite of what Im advocating. The core idea of eugenics is that there is a hierarchy of people who are inferior or superior that is rooted in biology and that inequalities are justified on that basis. Mine is an anti-eugenics approach seeking to use our knowledge of genetic science to build policies and social interventions that create more social equality. Sweeping genetic differences between people under the rug does not make the genome, as a systemic force causing inequality, go away. That genetic and environmental factors are braided together at every level is simply a description of reality.

How do you predict a persons educational attainment via their genome?It starts with a statistical exercise in correlation called a genome wide association study (GWAS). That takes many hundreds of thousands of people with similar genetic ancestry and measures tiny genetic differences of which there are millions scattered throughout their entire DNA sequences. It then looks to see which of those variants correlates with their number of years of schooling.

We then take the results and for a new persons genetic sequence add up that information to produce a single number, a polygenic score, that predicts how far they will go in school.

Crude though it is, the GWAS approach has found genetic variants that are correlated with going further in school. That isnt surprising we see evidence that theres a genetic influence on academic achievement in twin studies. Identical twins are more similar in how far they go in school than fraternal twins.

How many variants are we talking about and what is the size of the effect?Scientists have identified more than 1,000 genetic variants spread over the entire genome, each of which has a tiny effect. Taking the combined influence, it captures about 10-15% of the variance in educational attainment. The rate of college graduation is nearly four times higher for people who have a high compared with a low polygenic score. That competes with other variables we think of as important for educational attainment, such as family income, which has an effect size of about 11%. But it is still lower than the twin study estimate that about 40% of the variation in educational attainment is due to genes.

Can we say differences in educational attainment are caused by our DNA? Correlation does not equal causation and we know the environment makes a huge difference.Were reasonably certain at this point that the causal genetic influence is not nil. It is the size that is at issue. There are questions with the twin studies about whether they are attributing to genes what should really be claimed by the environment. And for polygenic score studies, people may just happen to differ genetically in ways that match environmental factors, and it is really those that are driving the effect.

More confidence in our conclusions comes when we get similar answers with different methods. Polygenic score studies within families are now also suggesting genetic cause. For example, studies of siblings who are raised in the same environment, but who are more different in their polygenic scores, show that these siblings have more different life outcomes.

Are people who have these genes more intelligent?The word intelligence is a lightning rod, because it is so easily misrepresented as being a marker of all human skill. But its clear that formal schooling in the US and UK reinforces a very particular type of reasoning. And it is the same type of reasoning that IQ tests also pick up on.

But we have also done a genetic study that found there is a basket of non-cognitive, personality related abilities helping pull people through school being conscientious and open to new experiences, for example. Anything that makes you more likely to get to the next stage of your education, to the extent that is reflected in your biology, a GWAS is going to pick it up. Importantly, people with these genes dont have good genes. They have genetic variants that happen to be correlated with going further in school as it is currently constructed.

Will we be rushing to read our childrens genomes to discover their polygenic scores in the future?Peoples imaginations jump to this world of individualised testing and tailored interventions. I dont think this knowledge is best used as a diagnostic tool about an individual person. There is always a danger that people will be given bad or incomplete information. I want to use genetics as a way of seeing whats happening within our environments and social structures better.

How should this knowledge be applied, then?One of the most useful applications is in improving the basic research we do to design our wider policies and interventions for everyone. There are many policy initiatives, and more are being proposed all the time. But their research base is limited because it assumes children only receive environments from their parents, and not anything genetic.

Consider, for example, policies to close the famed word gap, which is the estimated 30-million word difference in what poor children versus children from high income families hear before they turn three. The jury is still out on whether word gap interventions will be effective, but one glaring problem is the same vocabulary outcomes that are allegedly the outcomes of being exposed to more speech could also be the result of genetics. Parents and children share genes and the same genes that are associated with adults educational attainment and income are also associated with early acquisition of speech and reading in their children. Before we spend millions on interventions designed to change a parental behaviour in the hopes of improving child outcomes, it would be prudent to at least check this effect out.

Ruha Benjamin also suggested the hunt for more data to explain things just ends up being a barrier to acting on what we already know we need to do to fix the academic achievement gapI disagree that we already know what to do. If you look at meta-analyses of educational interventions, you see most of their effect sizes are zero. Most of the things we try in education, even when they are well intentioned and well funded, make no difference to students lives. It is a fiction we have this army of effective, scalable solutions just waiting in the wings. Figuring out what works for whom and when is very hard. The risk of not talking about genetics is continuing the status quo, where we are much less effective at intervening than we could be.

The Genetic Lottery: Why DNA Matters for Social Equality will be published by Princeton University Press on 21 September (25). To support the Guardian and Observer, order your copy at guardianbookshop.com. Delivery charges may apply

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Kathryn Paige Harden: Studies have found genetic variants that correlate with going further in school - The Guardian

Endometriosis treatment: Up to 10 percent of women experience endometriosis worldwide. The condition is chronic, extremely painful, and can result in infertility. Endometriosis happens when tissue similar to the lining of the womb (the endometrium) grows outside of the womb, in the abdominal cavity and sometimes on the ovaries and the fallopian tubes. These tissues respond to the hormonal signals of the menstrual cycle just like the endometrium does, which can cause severe pelvic or period pain.

How and why endometriosis develops is unknown and currently theres no cure. While treatments such as painkillers, surgery and even hormonal contraceptives are available, they dont always work, and many women find them to be insufficient.

But our recent collaborative study might have brought us one step closer towards finding a potential new target for treatment. We have discovered that DNA variations in the gene that produces the protein neuropeptide S receptor 1 (NPSR1) occur more often in women with endometriosis than in women who dont have the condition. NPSR1 plays a role in the transmission of nerve signals and in inflammation.

Our team at Oxford University has been working for decades to understand what genes cause endometriosis. We initially began conducting our research after observing that the condition can run in families and that up to 50% of endometriosis risk in women is due to genetics. But finding the genes that cause the condition wasnt a straightforward task. Endometriosis is complex and influenced by many factors including a persons genetic make-up, the environment, and the way these two factors interact.

To see what was different in the genetic make-up of endometriosis patients, we analysed the genome the complete set of genes any person carries of women with endometriosis and a family history of the condition, and those without a known family history. We then compared their DNA to women without endometriosis. In total, we analysed the genomes from 32 families with at least three women who had endometriosis and 105 women without endometriosis. We also consulted another genetic dataset of more than 3,000 endometriosis cases and 2,300 controls.

The familial analysis at first narrowed the cause down to an area on chromosome seven, which contains around 100 genes. Only after further and more detailed DNA sequencing did we find that it was the NPSR1 gene that carried significantly more harmful variants in women with endometriosis than other genes within the chromosome seven area. Women without endometriosis tended to have the normal NPSR1 gene more often.

To further confirm these findings, our collaborators at the University of Wisconsin-Madison and Baylor College of Medicine then checked DNA variations in a colony of rhesus macaques. These monkeys have periods like humans do and also get endometriosis. Sure enough, we found that changes within the same region on the macaque equivalent of human chromosome seven occurred more often in monkeys with endometriosis.

After confirming this link, the next step of our research was to test whether shutting down the activity of NPSR1 had any effect on inflammation associated with endometriosis. To do this, we first conducted experiments using cells, then mice. Our team and our collaborators at German pharma group Bayer found that if we shut down the activity of NPSR1 in immune cells, they became less responsive and produced less of a protein that normally drives inflammation. The mice in turn showed diminished inflammation and were in less pain than without the treatment.

However, the drug we used in these experiments is whats known as a tool compound meaning its only approved for use in cell and animal experiments, but is not able to be used on humans. The next step of research will be finding a drug that can be used in humans to similarly shut down NPSR1 activity, and see whether doing so also reduces symptoms of endometriosis.

Theres still a whole lot we dont know, though. For example, how exactly is NPSR1 connected to endometriosis and what does it do (or not do) that leads to inflammation and pain? It will also be important to uncover how DNA variants of NPSR1 affect the proteins function, and in which tissues.

Interestingly, NPSR1 also has a role in inflammation that occurs with other health conditions, including asthma and inflammatory bowel disease. Its also found in certain regions of the brain, where it has effects on anxiety and behaviour. This could mean that NPSR1 could play a role in the perception of pain, and in the anxiety that goes along with endometriosis.

Chronic suffering and exposure to pain also changes the brains architecture meaning the wiring of the brain cells and nerves respond differently and change over time. It might also be possible that the connection of NPSR1 to endometriosis happens not just in inflammation and abdominal pain, but also in the brain itself. This is another aspect of NSPR1 that will need to be explored.

Regardless, our research has shown that shutting down this receptor eases pain and inflammation in mouse models of inflammation and endometriosis. This opens up the future possibility for developing drugs against NPSR1 that would ease symptoms of endometriosis without shutting down the menstrual cycle, and potentially alleviate pain for millions of women.

Krina Zondervan, Professor, Reproductive and Genomic Epidemiology, University of Oxford and Thomas Tapmeier, Senior Research Fellow in Womens Health, Monash University published this article first on The Conversation.

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Endometriosis Treatment: Study On Linkage With Genome Offers Hope - SheThePeople

DUBLIN--(BUSINESS WIRE)--The "The Next Generation Sequencing Markets for Reproductive Health Testing in China" report has been added to ResearchAndMarkets.com's offering.

This report analyses the market trends influencing the demand for NGS for reproductive health testing in China. The market segments by application include Carrier Testing, PGT, NIPT, and New-born testing. The report also includes an assessment of the global market trends wherever the insights can be useful to assess China market trends. It covers a detailed analysis of the leading market players and their response to the impact of COVID-19 to their business.

China was part of the Human Genome Project that was completed in 2001. Since then, there has been significant investments in the genomics field by the government as well as different market players. This has helped the country to maintain a critical mass of skilled manpower who could drive genomics research and its applications in the country.

Reproductive health testing is one of the major application segments for NGS, where the demand for genomic testing is growing at a fast pace during the past couple of decades. Genomic technologies such as PCR and microarrays have fundamentally changed the landscape of reproductive health testing.

Currently, the advent of NGS-based high throughput sequencing methods is changing the market landscape at an accelerated pace. Some of the key factors driving the acceptance of NGS in this market include improvements in affordability, ease of use, and data analysis capabilities. There has been a significant reduction in the cost of sequencing per base during the past five years, globally.

China has also witnessed a similar trend in the domestic market. In fact, the leading NGS players in China offer NGS products and services at highly competitive rates compared to their counterparts in developed countries. The government has played a critical role in this aspect, by introducing favourable government policies and offering financial support to market players. Another key factor is the relatively lower manpower costs available in the domestic market.

Automated NGS workflow solutions have played a major role in the adoption of NGS by clinics and hospitals. Integration of the sequencing process with automated sample preparation, library preparation and data analysis steps has helped laboratories to scale up their NGS services and offer them at reduced service fees. The advancement in data analysis solutions is another factor that has enabled adoption of NGS by IVF clinics and hospitals.

Significant challenges still exist for NGS platforms that limit their growth potentials in the reproductive health testing segment in China. For instance, the cost of NGS-based tests is still much higher compared to the cost for other genomic platforms. For the NGS testing service providers, the large capital investment required to develop NGS infrastructure is another challenge.

In addition to the initial costs associated with establishing NGS workflows, the laboratories need to budget for the high recurring costs of consumables as well. Significant investments are needed for hiring and retaining a skilled workforce as well, who are trained for conducting NGS operations effectively. The costs for maintaining large data storage and data analysis facilities can also increase the budget needed for NGS service providers for including NGS tests in their portfolio.

The demand for NGS-based PGT is expected to drive the overall demand for NGS-based reproductive health testing at a fast pace in China. NIPT is the largest market segment within, and its demand is expected to continue at a CAGR of over 20 percent. As the government has introduced relaxations on China's one-child policy, there has been a significant growth in the demand for IVF, which in turn is expected to positively influence the demand for NGS-based reproductive health testing.

Overall, the market is expected to grow at a CAGR of over 30 percent between 2021 and 2026. The growth is expected to continue across all the market segments as acceptance of NGS increase among the end-users and new diagnostics enter the market.

Key Topics Covered:

Market Overview

The IP Landscape

The Regulatory Landscape

The Reimbursement Landscape

Products and Services Relevant to Reproductive Health Testing in China

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/lsgkk6

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Next Generation Sequencing Markets for Reproductive Health Testing in China, 2021 Report - ResearchAndMarkets.com - Business Wire

Assessment of the Two Hypotheses.

For the purpose of understanding the evolution of the plague bacteria, more than 100 ancient Y. pestis genomes have been published to date. The last 17 were recently reported during a short period by four distinct research groups (79, 12). Using most of the ancient genomes (criteria for exclusion are described in Methods), along with 499 modern ones, we present here the most updated phylogeny (Fig. 1).

Phylogeny and archaeological site locations of ancient genomes. (A) A maximum likelihood phylogeny was obtained with 574 genomes of Y. pestis (including 75 ancient genomes) involved based on 12,608 SNPs. The numbers at each node indicate the bootstrap values of 1,000 replicates. Branches highlighted in blue correspond to the second pandemic, which is subdivided in three groups: the 14th to 15th century group, which also includes the Black Death and the Pestis secunda (1,357 to 1,366) strains; the 15th to 17th century group; and the 18th century group (which also includes the BED genomes for homogeneity). Branches in purple correspond to the first Pandemic, and branches in green correspond to the prehistoric plague. The ratio between the depth of pla and that of the entire pPCP1 plasmid for all ancient genomes is shown in the rightmost heatmap, with a color scale ranging from 0 (dark blue) to 130+ (dark red). (B) Geographic distribution of the three waves during the second pandemic.

The updated phylogeny confirms the almost clonal nature of the Black Death strains in comparison to all other lineages of the second plague pandemic, including the strains from the Pestis secunda [Ber37 and Ber 45, The Netherlands (6), and BolgarCity2370, Russia (3)], which are placed on Branch 1 [see also London-Ind6330, United Kingdom (3)], as well as to all other strains, which are placed on the postBlack Death branch. There is general agreement that the postBlack Death branch was hosted in a novel wild rodent reservoireither in Europe or outside Europe (38, 12, 14). The original hypothesis (Hypothesis 1) claims that such a plague reservoir existed in Western Europe (15), perhaps in the Alps (16). However, a newer hypothesis (Hypothesis 2) claims that the plague reservoir was in Asia, possibly close to Eastern Europe (6, 7, 9, 11, 13).

In order to more easily view the phylogeny from the second plague pandemic and to better contrast the evidence for the two hypotheses, we generated two schematic figures (Fig. 2) and a table (Table 1).

Schematic comparison between the two main hypotheses for the interpretation of the Y. pestis phylogeny of the second plague pandemic. Historic and evolutionary information is included in the schematic figures. In addition to the symbols explained in the figure, we outlined in red the strains showing the 49-kb deletion. Pla decay (meaning both, full, or partial absence of the pla gene) is indicated by the names in bold.

Main differences between the two competing hypotheses proposed to explain the phylogeny of Y. pestis of the second plague pandemic; genomic and evolutionary, historical and archaeological, and ecological arguments are considered

Hypothesis 1 is supported by a phylogenetic analysis based on the currently available ancient genomes, which infers high posterior probability for a Western European source of the transmissions on the postBlack Death branch (SI Appendix, Fig. S1). However, as the dataset includes 41 ancient genomes from Western Europe against only 8 strains from Eastern Europe (including Gdansk and Riga), the proposed origins from Western Europe are likely to be biased toward a European reservoir due to a size-effect bias. Notably, the most basal genome LAI009 (4) (the Black Deaths lineage), Bolgar (at the root of Branch 1), and the most recent genome [CHE1 (7)] all originated from Western Russia, implying that they might have been closer to a putative Asian or Eastern European reservoir. This continuity does represent strong evidence in support of Hypothesis 2.

Using only genomic data, Hypothesis 1 might be seen as the most parsimonious hypothesis since it proposes an internal source for all western Eurasian outbreaks. However, for two locations (Pestbacken, Sweden 1710 [PEB10] and Marseille, France 1722 [OBS]), an origin from the Ottoman Empire is historically and archaeologically well supported (7). Thus, Hypothesis 1 needs to account for a back and forth spread, which reintroduced plague on two occasions to the Ottoman Empire and back again to Western Europe. Notably, none of the strains from the 18th century appear to have originated in Western Europe according to historical sources (7, 9).

Hypothesis 1 assumes the existence of a wild rodent plague reservoir in the Alps, which is not supported by ecological evidence (13). Instead, a study of more than 7,000 historical plague outbreaks and 15 tree-ring datasets (four of which from the Alps) found climatic signals in support of frequent reimportations of plague from Asia into Eastern and Western European harbors (13).

Intriguingly, only a few genotyped strains are nodes on the backbone of the postBlack Death branch: the strains of the Black Death itself, the strain from Gdansk 1425 to 1469, and the strains from London (BED, 16th to 17th century). While the strains of the Black Death were notoriously imported into Western Europe from the Mongol Empire via Caffa in Crimea (10), both Gdansk and London were very active harbors also in historical times and were very often hit by plague. Interestingly, Y. pestis was also recovered from a rat found in Gdansk. Although the genome is partial due to the different single-nucleotide polymorphism (SNP) profile, it is clear that the strain from the rat could not have infected the victim (Gdansk8) (9). Being a port, Gdansk may indeed have hosted diverse importations of infected rats in the period from 1425 to 1469, as it happened in European harbors during the third pandemic (17).

Hypothesis 2 is consistent with the ecological as well as with the historical evidence (Fig. 2 and Table 1). The only Western European subcluster, the Alpine cluster formed by LBG (Landsberg, Germany), STN (Stans, Switzerland), BRA (Brandenburg, Germany), LAR (Lariey, French Alps), and SPN (San Procolo a Naturno, Italian Alps), may naturally be explained by the circulation of soldiers and troops in Europe during the Thirty Years War (1618 to 1648), which made up human chains of transmission with historically documented epidemic events (12, 18, 19). For three strains (SPN from the Italian Alps, LAR from the French Alps, and BRA from Northern Germany), the relationship with the time of the Thirty Years War is historically and archaeologically documented (4, 7, 12). Human chains of transmission, which do not require the presence of rats to start and sustain an epidemic, might explain the circulation of the plague within Europe over long periods of time. They might be due to interpersonal contacts, crowding, infected parasites in clothes or goods (14, 20, 21), or contact with infected pets or fur (6). Several chains of human transmission within Europe could be reconstructed for cases of the last century (17, 22) as well as for the second pandemic (23, 24).

To better understand the evolution of Y. pestis, we examined two more mutations, which were recently discovered in ancient strains. In the most recent subclade of the second pandemic, starting with BED, there is a 49-kb deletion with unknown function. This deletion was also present in the last lineage of the first pandemic and, in both cases, might have accounted for the decline of the pandemic (4, 7, 25). We found the same mutation in the Rostov 2033 strain in the 18th century clade (Figs. 1 and 2). By contrast, a second strain found in the same cemetery in Rostov (Rostov 2039) has a different SNP pattern and lacks the chromosomal deletion.

Another mutation, the depletion of the pla gene on the plasmid pPCP1, has recently been proposed as the cause of the disappearance of the second plague pandemic in the 18th century (8) given that the pla gene is an important virulence factor of Y. pestis. We checked for the presence of the pla+/pla plasmids in all published ancient strains. The ratio in coverage depth between pla and the whole pPCP1 plasmid indicates the status of pla loss in an organism (Fig. 3). If the depth of pla is significantly lower than that of pPCP1, it might properly be concluded that the pla gene was lost in some pPCP1 plasmids. Our analyses show that the ratio of pla in the Black Death and postBlack Death genomes appears to be different when compared with the prehistoric and the first pandemic lineages (Fig. 1). We have also checked randomly selected modern Y. pestis genomes in different lineages, and their depth of pla and pPCP1 are quite consistent, indicating no other pla loss in modern plagues. By contrast, the generalized depletion of pla extensively observed during the postBlack Death era and at the end of the first pandemic (Fig. 1) seems to be consistent. Given that the sequencing data were generated by several different research groups, a systemic error during sequencing is unlikely.

The decay of the pla gene. (A) Depth plot of the pPCP1 plasmid in strain CHE1 using Integrative Genomics Viewer. The annotated genes of the pPCP1 plasmid are marked with blue bars. The average sequencing depth of whole pPCP1 plasmid is 195.65x, while the average sequencing depth of the pla region is 96.04x. (B) Group-wise comparison of the ratio between the depth of pla and that of whole pPCP1 plasmid among three waves of the second pandemic. Boxplots depict the upper, median, and lower quartiles of the ratios; individual dots indicate outliers that lie outside of 1.5 times the interquartile range; and vertical lines indicate the range of all ratios except for outliers. The P values of group-wise comparison using the Wilcoxon test are labeled on the top, two of which are statistically significant (P < 0.05). Data of B are provided in Dataset S4.

It seems that full pla strains were slightly depleted at the end of the second pandemic (8), with the same phenomenon at the end of the first pandemic. Notably, however, Rostov2033, one of the most recent genomes of the second pandemic, shows full read pPCP1 plasmids, whereas CHE, the most recent historical strain, shows very slight pla decay (Fig. 3). This observation is not fully in agreement with the proposed hypothesis that pla depletion contributed to the end of the pandemic. An alternative explanation for this phenomenon (8) is that the differences observed in the full pla plasmids might be due to different forms of plague. In particular, bubonic plague and pneumonic plague need the pla gene to develop, whereas primary septicemic plague does not (8). It seems that plague existed in all three forms, at least from the time of the first pandemic; however, this does not add any specific evolutionary information to the observed variability.

We propose an evolutionary hypothesis for the presence of lineages with pla decay. One of the optimized survival strategies for an emerging pathogen is to balance its virulence to the main host with its transmission strategy. This trade-off hypothesis was previously demonstrated for Y. pestis (26, 27). This mechanism would allow the bacterium to reduce virulence and enhance the time of survival of the host and, consequently, of the pathogen (28). After experiencing the Black Death and successive waves, the pla decay strains might have attempted to acquire a fitness advantage, reducing their virulence by increasing the time to death. Indeed, we observe among the victims only pla+/pla mixed strains, whereas pla lineages might have survived longer in the host population, providing a milder form of the illness. The Eastern European/Asia clade of the 18th century (including CHE1) further lost the 49-kb region, which can be the result of an extension of a virulence attenuated pattern. Such events of attenuated virulence might have occurred multiple times in the Y. pestis evolutionary history and left out host-adapted lineages, such as for 0.PE2 and 0.PE4 (29). Therefore, the possible virulence reduction caused by pla decay and loss of the 49-kb region is not necessarily the reason for the extinction of plague at the end of the first and second pandemics but might be the result of a form of adaptation to a new host, which may be the wild rodent in the putative Western European reservoir (Hypothesis 1), a new host in the Asian reservoir, or the human host (Hypothesis 2) as well as their vectors. We observed that the newly published strains from Lariey [French Alps (12)] do not show pla decay in contrast to other Alpine lineages (SPN). This evidence might exclude the hypothesis of an adaptation to a host in a Western European reservoir. Thus, we tentatively propose that this mechanism of pla decay would support the presence of human-to-human transmission chains mediated by human ectoparasites (fleas and body lice) during plague pandemics in Europe, the plausibility of which has previously been demonstrated (17, 22, 30), while the vector competence was supposed to be low (31).

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Assessing the origins of the European Plagues following the Black Death: A synthesis of genomic, historical, and ecological information - pnas.org

Thus, LuPSMA opens prostate cancer to theranostics, an exciting area of precision medicine.

In the New Precision Medicine Approaches in Advanced Prostate Cancer series, experts discuss the evolving spectrum of precision medicine in advanced prostate cancer. This series features a review of NCCN guidelines, genomic testing, nuclear imaging, PSMA, advanced disease, and the rapidly developing treatment landscape and emphasizes the potential impact of newer therapies on prostate cancer treatment.

In the first interview of the series, Neeraj Agarwal, MD, a genitourinary oncologist, director of the Genitourinary Oncology Program and the Center of Investigational Therapeutics, and professor of medicine and Presidential Endowed Chair of Cancer Research at the Huntsman Cancer Center of the University of Utah, Salt Lake City, discusses the role of genomic testing and imaging in the initial diagnosis, staging, and treatment of prostate cancer.

TARGETED ONCOLOGYTM: Could you discuss the current NCCN guidelines for initial prostate cancer screening and diagnosis?

AGARWAL: In the guidelines, the first step is to perform a digital rectal examination to confirm the clinical stage of prostate cancer. Thats followed by looking at the PSA [prostate-specific antigen] level, calculating the PSA density and PSA doubling time, and reviewing the diagnostic prostate biopsies or, if they have not been done, obtaining prostate cancer biopsies.

This is followed by a very important step: estimating the life expectancy of a given patient, using the validated tools on the NCCN guidelines website. This estimate is used to not overtreat those patients who are not likely to die because of prostate cancer. For instance, if somebody has major cardiovascular disease, heart failure, and a performance status of 3 and [is] diagnosed to have a prostate cancer, but his life expectancy turns out to be 1 or 2 years, is there any reason [for this patient] to undergo radiation therapy or surgery for his prostate cancer? This patient likely is going to die with prostate cancer and not because of prostate cancer. Hence, estimating the life expectancy is so important.

For the next step, we follow important changes in the recent NCCN guideline versions. These require us to obtain testing for high-risk germline mutations. If we come across a family history of high-risk germline mutations, such as BRCA1, BRCA2, or Lynch (MSH2) mutations; if the family history is suspicious for these mutations; or if there is intraductal and/or cribriform histology in an intermediate-risk patient, then the patient needs to be sent to a genetic counselor for pretest genetic counseling before undergoing germline testing. It should be noted that the intraductal and/or cribriform histology are known to be associated with increased risk of these mutations. Even if I dont see a family history of these genetic mutations, I still consider germline testing in many patients if they have high-risk clinical features. And, of course, obtaining a thorough family history when the patient is diagnosed for the first time is also very important.

This is the initial approach to screen and diagnose a patient with newly diagnosed prostate cancer or who is suspected to have prostate cancer.

TARGETED ONCOLOGYTM: The NCCN guidelines place staging as the next step. After patients are staged, who should undergo genomic testing?

AGARWAL: The NCCN guidelines lay out very nicely how to stage newly diagnosed patients into very low-, low-, intermediate-, high-, or very high-risk categories. Once staged, [patients at] very low risk usually are not required to have tumor-based molecular assays or genomic tests such as Decipher, Oncotype Dx prostate, and Prolaris. They are required to have a confirmatory prostate biopsy or an MRI of the prostate and, mostly, are candidates for active surveillance, so we can put [patients at] very low risk on the side. On the other side of the spectrum, we have [patients given a diagnosis of] very high-risk prostate cancer who are likely to have metastatic disease. If distant or regional metastasis [has] been found in the bone scan or the CT scan, [patients] obviously require systemic therapy. If they do not have metastatic disease, [patients] still require some kind of surgery or radiation or definitive therapy. So, we usually dont need these tumor-based molecular assays for patients who [have received a diagnosis of] very low- or very high-risk prostate cancer.

Anyone in betweenwhich includes low-, intermediate-, and high-risk patientsrequires one of these molecular assays, according to the NCCN guidelines, as long as they have a life expectancy of 10 years or more. And, again, we dont need any of this testing or definitive therapy if patients have a low life expectancy. Those patients are unlikely to die because of prostate cancer; theyre likely to die with prostate cancer.

TARGETED ONCOLOGYTM: You mention MRI, bone scan, and CT scan. What is the role of imaging in prostate cancer therapy?

AGARWAL: After the initial diagnosis of prostate cancer, depending upon the risk of the prostate cancerbut especially in those who belong to intermediate- or high-risk localized prostate canceraccording to the NCCN guidelines, we obtain a bone scan [and/or] a CT scan of the pelvis, plus or minus the abdomen Basically, we want to rule out regional or distant metastasis. For low-risk prostate cancer, the NCCN guidelines ask that we consider confirmatory prostate biopsy with or without a prostate MRI to establish candidacy for active surveillance. The NCCN guidelines have very specific indications on when to get imaging studies. But if you look at intermediate- and high-risk prostate cancer, when the risk of metastasis is higher, clearly there is a definite role of bone scan and CT scan, so the first step is to rule out metastasis.

TARGETED ONCOLOGYTM: For these low-, intermediate-, and high-risk patients who have long life expectancy and who dont have metastases, whats the role of genomic testing? Why is it done?

AGARWAL: Once you have ruled out [metastasis], and as long as these patients are wellhave a life expectancy of more than ten yearsthere are 3 genomic tests or tumor-based molecular assays which can be performed. The tests that are currently approved and widely utilized in the clinic are Decipher [Prostate], Oncotype DX [Genomic Prostate Score assay], and Prolaris. All of these are not done in 1 patient; 1 test can be offered to a patient. Patients who have [been given a diagnosis of] low-risk, intermediate-risk, [or] high-risk localized prostate cancer with a life expectancy of 10 years or more can be offered one of these tests.

What are these tests supposed to do? They are supposed to tell us, in those patients who do not have obvious evidence of metastasis on the scan, what is the likelihood of these patients [dying] of prostate cancer? What is the likelihood of these patients developing metastasis? What is the likelihood of these patients having non-organ-confined disease? Also, in [the] case of Decipher, the test can also be used after surgery; so, most of these tests are used after the biopsy, not after the surgery. But in the case of Decipher, we can use this test after the surgery if there are high-risk features present, especially to look for the role of radiation therapy in those patients.

Overall, what these tests are doing is that they are helping us in determining the likelihood of metastasis and death because of prostate cancer in our patients who are considered to have localized prostate cancer today. When you are doing this testinggenomic testingtheyre actually helping us in determining whether we should treat these patients with definitive therapy or [if] it [is] safe for these patients to undergo active surveillance That is one of the reasons we are doing this testing.

So, questions may be asked in this context. If you already [have] NCCN risk stratification in place, you have CAPRA [Cancer of the Prostate Risk Assessment] scores in place, why do you need these tests? Studies have shown that Decipher [Prostate], Oncotype DX [Genomic Prostate Score assay], and Prolaris testing can independently predict or correlate with metastasis and prostate cancerspecific mortality versus traditional NCCN risk stratification or CAPRA risk.

So, I think because of the independent nature of being able to predict prostate cancerspecific mortality, onset of metastasis, [and] onset of biochemical recurrence, there is a value of doing those tests.

TARGETED ONCOLOGYTM: Could you describe these tests in greater detail?

AGARWAL: These tests are done on biopsy specimens and are RNA-based. All of these independently predict risk of recurrence and metastasis, and risk of death because of prostate cancer.

In the case of Decipher, this is a whole-transcriptome assay [that] is looking at 1.4 million RNA covering more than 46,000 genes and noncoding parts of the genes. This is an oligonucleotide microarray, which is optimized for FFPE [(formalin-fixed paraffin-embedded) tissue specimen] addition. Its pretty easy to do the test. You can send out the tissue for tests to be performed in an external laboratory without having to worry about the degradation of the quality or quantity of tissue.

Oncotype DX [Genomic Prostate Score assay] is also used on the biopsy tissue. Oncotype DX is a quantitative RTPCR [(reverse transcriptionpolymerase chain reaction) test] for 12 prostate cancerrelated genes.

The third approved, widely utilized genomic test is Prolaris. This uses a quantitative RTPCR platform for 31 cell cyclerelated genes and 15 housekeeping genes.

TARGETED ONCOLOGYTM: How helpful are these NCCN-recommended genomic testsis genomic testingfor treating prostate cancer?

AGARWAL: These testsProlaris, Decipher [Prostate], and Oncotype DX [Genomic Prostate Score assay]are for patients who have local, organ-confined disease; who have [been given a diagnosis of] low-, intermediate-, or high-risk prostate cancer; and who have an estimated life expectancy of 10 years or more. They can help independently of the NCCN risk stratification or CAPRA risk stratification. These genomic tests can independently help our patients in deciding whether they want to pursue active surveillance or definitive therapy with surgery or radiation by telling them their risk of recurrenceeither biochemical recurrence or metastatic diseaseor their risk of dying because of prostate cancer.

Read the rest here:
The Role of Imaging and Genomic Testing in Prostate Cancer Therapy - Targeted Oncology