How do scientists predict the risk of humans suffering from multiple diseases?

In this article, the editor compiled a number of important research results, focusing on how scientists can predict the risk of humans suffering from multiple diseases? Learn with everyone!

In this article, the editor compiled a number of important research results, focusing on how scientists can predict the risk of humans suffering from multiple diseases? Learn with everyone!

Image source: www.

[1] bioon.

bioon.

doi: 10.

In a report in the online edition of Nature Communication on February 23, 2021, researchers described the performance of the polygenic risk score (PHS) for multi-ethnic patients-a mathematical estimate of the genetic risk of disease at a specific age.

[2] bioon.

bioon.

doi: 10.

The relevant research results were published in the journal JAMA Oncology; the researchers said that the research results may change practice and will provide oncologists with more information to help guide decisions about whether to provide hormone therapy for patients.

[3] bioon.

bioon.

doi: 10.

Dr.

[4] bioon.

bioon.

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"Since the initial outbreak of COVID-19 in New York City, we have found that the presentation and disease process of COVID-19 are heterogeneous.
We have used patient data to build a machine learning model to predict the outcome," the main researcher of the study One, Dr.
Benjamin Glicksberg, assistant professor of genetics and genomics at the Icahn School of Medicine at Mount Sinai, said: “Now, in the early stages of the second wave of epidemics, we are better prepared than before.
We are currently evaluating how these models are.
Help clinicians manage patient care in practice.
"

[5] bioon.
com/article/6779739.
html">Nat Biomed Engine: Scientists are expected to use artificial intelligence technology to predict the risk of cardiovascular disease in the population

bioon.
com/article/6779739.
html">Nat Biomed Engine: Scientists are expected to use artificial intelligence technology to predict the risk of cardiovascular disease in the population

doi: 10.
1038/s41551-020-00626-4

doi: 10.
1038/s41551-020-00626-4

Recently, in a research report published in the international journal Nature Biomedical Engineering, scientists from Singapore’s National Eye Center and other institutions have developed a new method using artificial intelligence technology to predict the risk of individuals suffering from cardiovascular disease.
The article In this article, the researchers describe how to use retinal blood vessel scans as a data source for a deep learning system, thereby teaching the system how to recognize signs of cardiovascular disease in the population.

For more than 100 years, clinicians have been observing patients’ eyes to look for changes in retinal blood vessels.
These changes can reflect the effects of individuals suffering from high blood pressure over a period of time, and such effects may be the imminent occurrence of cardiovascular disease.
Over time, medical scientists have developed special instruments to help ophthalmologists better observe the parts of the eyes that are most susceptible to high blood pressure, and can use it as a key to the diagnosis of hypertension patients Part, but tools such as these still require medical professionals to make the final decision on the patient’s diagnosis.
In this latest study, researchers can teach the artificial intelligence system to recognize the same types of symptoms in the body of the population, which does not require humans.
Intervene artificially.

Image source: Nature , 2020, doi:10.
1038/d41586-020-02749-9

Nature

[6] bioon.
com/article/6779488.
html">Nature: Measuring DNA mutations accumulated in a single skin cell can predict the risk of melanoma

bioon.
com/article/6779488.
html">Nature: Measuring DNA mutations accumulated in individual skin cells can predict the risk of melanoma

doi: 10.
1038/s41586-020-2785-8

doi: 10.
1038/s41586-020-2785-8

According to a new study that detects DNA mutations in individual skin cells, researchers from the University of California, San Francisco and the University of Utah pointed out that long before any suspicious moles are found, it is possible to estimate the deadliest skin cancer --- melanin Tumor --- risk.
Related research results were recently published in the journal Nature.
Skin damage caused by sunlight accumulates over time, but is often invisible to the naked eye.
However, the DNA in skin cells will also accumulate damage under solar ultraviolet radiation for many years, and this damage can be measured.

Researcher Dr.
A.
Hunter Shain said that the genomic method for detecting skin damage developed in this study can be used to estimate the baseline melanoma risk of individuals in the general population, and suggest how often dermatologists should screen someone for cancer.
Suggest.
Shain said, "It turns out that many cells in the so-called normal skin are full of mutations associated with melanoma, which are the result of sun exposure.
Melanoma usually only appears after decades of mutational damage, but Some people are at greater risk than others.
With the technology we have developed, those who accumulate the most mutations can be monitored more closely and can seek to better protect themselves from the sun.
"

[7] bioon.
com/article/6778141.
html">Cell: The identification of more than 7,000 genetic regions that control the characteristics of blood cells in the human genome is expected to predict the risk of rare and common blood diseases in the population

bioon.
com/article/6778141.
html">Cell: The identification of more than 7,000 genetic regions that control the characteristics of blood cells in the human genome is expected to predict the risk of rare and common blood diseases in the population

doi: 10.
1016/j.
cell.
2020.
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008

doi: 10.
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2020.
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Now two large-scale genetic studies have identified most of the genetic mutations that affect the important medical characteristics of the body’s blood cells.
Recently, a research report published in the international journal Cell, from the Sanger Institute of the University of Cambridge, UK, and others Scientists from 101 research institutions around the world have studied thousands of participants and have identified more than 7,000 regions in the human genome that can control the characteristics of blood cells, including the number of red blood cells and white blood cells.

In the article, researchers explain for the first time how a person’s genetic makeup induces blood disorders.
The relevant research results may help researchers use genetic scoring tools to predict the risk of individuals suffering from blood disorders in the clinic.
Blood cells play a very critical role in human health, including the body’s immune response, oxygen transport, formation of coagulation to prevent blood loss from wounds, etc.
Blood disorders such as anemia, hemophilia, and blood cancer may cause global health Important burden.
Many of these diseases are regarded as extreme conditions of the normal biological state, such as anemia.
The patient's body often induces insufficient oxygen supply due to too few red blood cells.
These extreme conditions may also be caused by small mutations in the body's DNA, and some of these mutations It also increases the individual's risk of illness.

[8] bioon.
com/article/6777309.
html">Int J Cancer: Scientists are expected to use the polygenic risk scoring system to predict the risk of common cancers in the population

bioon.
com/article/6777309.
html">Int J Cancer: Scientists are expected to use the polygenic risk scoring system to predict the risk of common cancers in the population

doi: 10.
1002/ijc.
33176

doi: 10.
1002/ijc.
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Recently, in a research report titled "Evaluating polygenic risk scores in assessing risk of nine solid and hematologic cancers in European descendants" published in the International Journal of Cancer, scientists from Vanderbilt University and other institutions Significant progress has been made in the field of prevention research.
In recent years, the global cancer incidence and mortality rate are increasing rapidly.
Although the reasons behind are more complicated, scientists are still striving to find those high-risk groups who are easy to benefit from cancer screening.
Wei Zheng, MD, said that in this study, we used polygenic risk scores (PRS) to predict the risk of common cancers in the population, including prostate cancer, breast cancer, and colon cancer.
The polygenic risk scores summarized The combined effect of multiple gene mutations.

Today, researchers are using new technology to evaluate nine less common cancers, including melanoma, glioma, and chronic lymphocytic leukemia, which account for approximately 24% of cancer deaths worldwide.
In the article, the researchers studied 400,807 people of European ancestry from the British biobank, and conducted a genome-wide association study on the data collected from these groups.
The researchers conducted a study through the polygenic risk scoring system and found that, 63% of participants more than tripled their risk of developing at least one type of cancer.

[9] bioon.
com/article/6776925.
html">Nat Med: New method can predict the risk of infants suffering from type I diabetes in the future

bioon.
com/article/6776925.
html">Nat Med: New method can predict the future risk of type I diabetes in infants

doi: 10.
1038/s41591-020-0930-4

doi: 10.
1038/s41591-020-0930-4

In a recent study, scientists developed a new method for predicting type 1 diabetes in infants.
In a study published in Nature Medicine, scientists at the University of Exeter and the Pacific Northwest Research Institute used TEDDY data to track 7,798 children at high risk of developing type 1 diabetes after birth.
In addition, based on an analysis method developed by them, a variety of factors are combined to evaluate the risk of children suffering from type 1 diabetes.

The research team found that the new combination method greatly improved the prediction of which children will develop type 1 diabetes, which may provide families with better diabetes risk counseling services.
Most importantly, this new method doubles the efficiency of the procedure for screening newborns to prevent potentially fatal ketoacidosis, which is the result of type 1 diabetes, in which insulin deficiency can cause the blood to become excessive.
Acidic.
Identifying which children are most at risk will also benefit clinical trials of drugs that are expected to prevent the disease.

[10] bioon.
com/article/6758394.
html">Cell Host & Micro: Intestinal flora may help improve the prediction of type 2 diabetes risk

bioon.
com/article/6758394.
html">Cell Host & Micro: Intestinal flora may help improve the prediction of type 2 diabetes risk

doi: 10.
1016/j.
chom.
2020.
06.
004

doi: 10.
1016/j.
chom.
2020.
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The composition of the intestinal microbiome is very complex and varies from individual to individual.
Various factors such as environmental factors, lifestyle, genetic factors, and diseases will affect the intestinal ecosystem of beneficial intestinal flora; recently, an article was published in In a research report on the international journal Cell Host & Microbe, scientists from the Technical University of Munich and other institutions have found through research that the intestinal flora may improve the prediction of the risk of type 2 diabetes in the population.
In this article, the researchers analyzed the importance of daytime-dependent fluctuations in the gut microbiome associated with type 2 diabetes.
They analyzed more than 4,000 people.
At the same time, this research is the first research in this field based on a large-scale prospective human cohort.
Relevance research.
Dr.
Dirk Haller said that in order to be able to clarify whether changes in the gut microbiome are related to multiple diseases of the body, we need to conduct so-called prospective cohort studies.

In these prospective cohort studies, researchers were able to analyze cross-sections of the participants.
However, none of the participants showed any signs of disease.
Over time, the researchers retested these participants, based on In this way, researchers will be able to discover whether a certain observation is representative of predicting the occurrence of a disease in the future.
When a particular intestinal flora cannot keep up with the circadian clock, which means that its number and function no longer change with the time of the day, then it may become a predictor of the onset of potential type 2 diabetes.
Know this or It can help improve the researcher's diagnosis and treatment of type 2 diabetes.
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More exciting inventory! Stay tuned! More exciting inventory! Stay tuned!