July 23, 2024

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Science: Still 9 major issues to be resolved on Human Genome Project

Science: Still 9 major issues to be resolved on Human Genome Project



Science: Still 9 major issues to be resolved on Human Genome Project. 

Science: The 20th anniversary of the completion of the Human Genome Project, there are still 9 major issues to be resolved.


The Human Genome Project (HGP), which was officially launched in 1990, and the Manhattan Atomic Bomb Project and the Apollo Moon Landing Project are called the three major scientific projects.


As a large-scale, transnational and interdisciplinary scientific exploration project, the purpose of HGP is to determine the nucleotide sequence of 3 billion base pairs contained in the human chromosome, map the human genome, and identify the genes it contains. And its sequence, so as to achieve the purpose of deciphering human genetic information.


In 2001, the release of the human genome working draft was considered a milestone in the success of HGP. In 2021, 20 years have passed since the publication of the Human Genome Working Draft.


In these 20 years, more and more countries and teams have joined this plan. The participation of biotechnology companies has gradually reduced the cost of sequencing and improved the speed and throughput of sequencing. The continuous increase in the amount of sequence data has also promoted the development of mathematical and computational tools used to assemble and annotate data.


On February 5, 2021, Science magazine published a series of articles on the 20th anniversary of the release of the Human Genome Working Draft. While celebrating the 20th anniversary of the release of the human genome working draft, Science also raised a series of issues facing HGP and published an article under the title: “Complicated legacies: The human genome at 20”.





Summaried contents as below: The spirit of data sharing is more important than ever


In February 1996, HGP leaders gathered in Bermuda to discuss

“Bermuda Principles”, that is, agreeing to submit genome sequencing data exceeding a certain size to a public database within 24 hours after generation.

The “Bermuda Principles” of public data is the basic heritage of the first human reference DNA sequence produced during the HGP. Since the 1990s, these principles have become the touchstone of open science.


Although many participants shared their data, there are still many people who only shared the data with a small group of users, and even kept the data after the relevant papers were published.

The uniqueness of the “Bermuda Principles” is that it hopes to publish the genetic sequences of all HGP-funded projects to any online user within one day. However, implementing this policy is not easy.


Need to promote the “Bermuda Principles”.

Publishing data within 24 hours is still a goal, not a strict requirement. The flexibility of the “Bermuda Principles” allows smaller centers to participate in the plan, while also allowing the project to adapt to the incompatible policies of Germany, France, Japan, and the United States at the time. Since then, the “Bermuda Principles” have been adapted to different communities and have provided inspiration for many other principles.


Sharing data can save lives.

For example, rapid data sharing is crucial in the current COVID-19 crisis. The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome sequence was quickly determined and announced on January 10, 2020, which is the beginning of vaccine development and diagnostic testing.




Lack of diversity hinders the prospects of genomics

If we still focus on the genomes of European descent, it will damage the long-term global development of human genomics and hinder the understanding of human history and biology.


Although all people have a common recent origin in Africa, and the genetic difference between two individuals is also very small, this can be transformed into about 3 million individual genome mutation points, and these human genetic variants (HGV) are not Randomly distributed.


We have long known that we cannot “find the root” based solely on the geographical distribution of the genome, but the current genomics research is still mainly focused on the genome of the European region. Presumably, this is because individuals of European descent are tall, distinctive, and data available.


But now, the cognition of the diversity and representativeness of individual genes has increased from the scope of specialized research to a broad understanding of genomics.

Without exacerbating health inequality, in order to deploy genomics-driven technologies and clinical and public health methods globally, we must study individuals of different ancestry and geographic backgrounds.


Of course, everyone is also beginning to realize the impact of increasingly diverse populations on genomics, the TOPMed project, the International Common Diseases Alliance, Human Genetics and Health in Africa (H3Africa), the Million Veterans Project, GenomeAsia and other projects, and all of us for research The development of genetic diversity and inclusiveness has contributed.




Unleash the potential of algorithmic biology

In 2000, Jim Kent, a graduate student at the University of California, Santa Cruz, created the first genome assembly software. GigAssembler puts together millions of DNA sequence fragments produced in laboratories around the world to “represent” the human genome.


Almost at the same time, Celera Genomics acquired the algorithm software company Paracel. Paracel has specially designed text matching hardware and software (TRW fast data finder), which can search for genes in the vast genome space.


To unravel the messy genome letters, you need to quickly and accurately search for the specified sequence in a large genome space, This requires new forms of training and subject expertise. Physicists, mathematicians, and computer scientists have brought methods such as linear programming, hashing, and hidden Markov models into biology.


Since 2005, the development of next-generation sequencing technologies similar to Moore’s Law has produced more and more data and requires faster indexing and search algorithms. People in the biology industry have borrowed the “big data” method, which has also promoted the frontier development of computer science research.


The combination of algorithmic bioinformatics and computational biology has also given birth to new institutional forms and new markets for biomedicine. Statistics-driven “data-driven biology” has been equipped with a new medical-industrial complex, which is expected to achieve personalized and “precise” forms of diagnosis and treatment.


An algorithmic pipeline that compares the genotype of an individual with reference data produces a series of predictions about future health and risks.  At the same time, people have always been worried that the collection of genomic data and information will expose too much of our personal information and expose us to new discrimination.




The value and affordability of precision medicine

Precision medicine uses genetic information to prevent and intervene human diseases. Usually what we care about is whether we can afford the technology, but we rarely pay attention to its value. Its value can be measured by the health outcomes obtained for every dollar spent on interventions.


Ideally, precision medicine interventions can save costs and improve results. But most healthcare interventions produce better results at higher costs, and the same is true for precision medicine.


How to resolve the contradiction between the value and affordability of precision medicine requires further discussion and advancement.


Finding the relationship between the value generated by precision medicine and affordability requires data on total costs and outcomes, as well as potential cost offsets, but these data are difficult to capture. Because the cost is usually incurred in advance, it gradually produces beneficial results over time.


Emerging precision medical tests can be used to screen large numbers of people, Including genome sequencing of all newborns, liquid biopsy to screen for cancer in routine primary care visits, and predictive testing for Alzheimer’s disease in adults. These interventions may bring huge benefits, but may require a lot of upfront expenditure.


Although various methods have been developed to integrate affordability and value, cost-benefit analysis usually does not examine budgetary impact, which can lead to incomplete or conflicting conclusions.

More and more considerations about affordability and value are not the result of methodological progress, but more attention to how to ensure sustainable and effective health care.


The positive result of this is to better define and quantify research on affordability and value based on existing data.

Most technologies can only realize their potential if they are reasonably priced and have high value.




The entanglement between race and genetics should end

After the first publication of the working draft of the human genome, researchers confirmed what many scholars have known for decades:Race competition is a social structure, not written in our genes.


However, the emergence of the human genome map did not stop this race, but aroused new interest in people based on ethnic genetic differences.


The latest genetic research results published on the white supremacist website led to another statement issued by the American Human Genetics Society in 2018.  Condemned that claims of racial purity based on genetics are “scientifically meaningless”  .

None of these histories has restricted the search for genetic differences between races and the genetic explanations of various race differences, which in turn has caused the public to continue to be confused about race and genetics.


It’s time to end the entanglement between race and genetics,  And strive to have a new understanding of human unity and diversity. Generally, there are two methods that can help guide innovative research questions and methods. These questions and methods no longer rely on racial classification like human biology.


First, genetic researchers should stop using race as a biological variable that can explain differences in health, disease, or response to treatment. Regarding race as a biological risk factor conceals how structural racism has biological effects and causes health differences among racialized populations.


Researchers must exercise caution so as not to make harmful epigenetic processes seem permanent and inevitable, and should divert attention from the structural inequality that caused the problem in the first place.


Second, researchers should stop using the white European standard for human genes and should study broader human genetic variations.   

For example, the project that has been studying the DNA of the various ethnic groups on the African continent to expand the genetic database shows that these populations are the most genetically diverse populations on the planet, and refutes the fallacy that there are genetically distinguishable black races.


The purpose of diversified biomedical research should not only be to discover innate genetic differences between ethnic groups, but should enable people from different ethnic groups to have equal opportunities to participate in high-quality research, ethical research (including clinical trials) and share the benefits. And provide scientists with abundant resources to better understand human biology.


In this way, genetic research can promote more personalized diagnosis and treatment, instead of relying on rough medical decisions based on patient ethnicity.




Genetic privacy issues in the post-epidemic era

In 2007, only Craig Venter and Jim Watson had their entire genomes sequenced. Today, more than 30 million people have access to its detailed genome data set. The democratization of genomic data helps family reunification, fights against racism, and promotes genetic quality, but it also makes the scope of surveillance larger.


The correlation of DNA variation between distant relatives allows relatively small databases to identify most of the population, even if the person’s data is not in the database. With the emergence of consumer genomics and third-party websites that allow participants to upload genomic data, it has become easier to collect and access DNA data.


We believe that the outbreak of the COVID-19 epidemic will accelerate genetic monitoring. People may be monitored at airports arriving at the border. Institutions can use the epidemic control infrastructure to build a DNA database of all entrants. Such a database can amplify genetic information through family connections and identify a large part of the population of entrants.


With the expansion of third-party genetic databases, basically everyone with appropriate technical skills can identify personal genetic information. and so We also need to establish guidelines for the use of genetic monitoring technology. Open discussions are critical to further formulating policies to use the power of the genome revolution to benefit the public.




Emerging Ethics in Native Genomics

Although genomics research has made great progress in the past two decades, some local aborigines may not think so. In many studies that have collected aboriginal biological materials to study diseases, medical characteristics and population origins, many studies have not benefited participants or their communities, and some studies have even caused damage ,  Such as exacerbating discrimination and harmful prejudice or challenging cultural beliefs.


Indigenous people may not benefit from research in fields such as precision medicine and pharmacogenomics, and health differences may still remain unresolved. At present, aboriginal scholars are formulating guidelines to solve these problems, hoping that the research can make the rights and interests of the local aboriginal people more equitable and benefit their communities.


Paying more attention to the rights and interests of the indigenous people and enhancing their participation and ability may reduce prejudice and provide more relevant and useful research for all.




Polygenic risks in a diverse world

Polygenic risk score (PRS) is a system that aggregates the small effects of multiple polymorphisms in a person’s genome into one score. PRS can be calculated by obtaining any phenotype with allele-wide association data.


In medicine and public health, PRS can be used to select treatments, initiate additional risk screening, or promote behavior change. So far, PRS has been proven to play a role in diseases such as blood pressure, obesity, diabetes, depression, schizophrenia and coronary heart disease.


PRS can also show the complex intersection between race and ancestry in genomics, supplementing the gaps in previous work. Recent analysis shows that In 26 previous studies, people whose poverty reduction strategies have deteriorated significantly were mainly of European descent, And there is not enough data to evaluate the performance of groups in other regions.


The researchers attributed this result to the underrepresentation of non-Europeans and ethnic minorities in the data set used to develop the PRS. Compared with the people included in most genome data sets, the ancestors of ethnic minority groups often come from outside Europe.


In order to make the different predictive capabilities of PRS better, researchers have developed some PRS specifically for people of African descent, And genomics scientists are considering whether “each ethnic group needs ancestor-specific PRS.”


If one does not consider how social inequality affects health and how race imperfectly replaces ancestors, it is easy to fall into ignorance of race on the impact of genetic ancestry on PRS. Society needs a multidisciplinary approach to develop and implement PRS for different groups.


Otherwise, the ancestor-specific PRS may reinvigorate people’s misunderstanding of race as a genetically different group, and encourage people to mistakenly believe that the distribution of traits between ethnic groups is mainly caused by genetics. This belief is essential to white supremacy and racist medical practice.


Injustice in science may occur because certain groups of people are not included, but unjust tolerance can also lead to injustice.




The risks of genome surveillance and how to stop

Although in some cases, the use of DNA profiling can help to identify the suspect and release the innocent. However, in the past two decades, there has been a surge in the preservation of human genetic information in the form of national DNA databases worldwide, which has raised important human rights issues.


European and American landmark court decisions set some restrictions on the collection and retention of DNA data, but these decisions are far from the comprehensive regulations we need.


The right to privacy is a basic human right. Worldwide, the unregulated collection, use, and retention of DNA has become a form of genome monitoring.


As the price of detection technology becomes lower and lower, and the adoption of surveillance becomes more and more widespread, huge risks of genome surveillance also arise. Governments should reform supervision laws and draft comprehensive privacy protection measures to strictly supervise the collection, use, and retention of DNA and other biometric identifiers.


If they do not meet the international human rights standards of legality, proportionality and necessity, such activities should be prohibited.





Science: Still 9 major issues to be resolved on Human Genome Project

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