Unraveling the Genetic Secrets of Disease Risk: The All of Us Research Program's Discovery

The All of Us Research Program is a longitudinal cohort study that aims to enroll at least one million individuals across the USA.
The program has already collected genetic data from 245,000 clinical-grade genome sequences and identified more than 275 million never-before seen DNA variants. These variants are located in areas that may be tied to disease risk and could explain why some people are more prone to certain diseases than others.
The program is unique in its diversity as 76% of participants come from communities historically underrepresented in biomedical research, including African Americans, Hispanic/Latinx individuals, Native Hawaiians/Other Pacific Islanders and Asian Americans.
Unraveling the Genetic Secrets of Disease Risk: The All of Us Research Program's Discovery

The All of Us Research Program is a longitudinal cohort study that aims to enroll at least one million individuals across the USA. The program has already collected genetic data from 245,000 clinical-grade genome sequences and identified more than 275 million never-before seen DNA variants. These variants are located in areas that may be tied to disease risk and could explain why some people are more prone to certain diseases than others. The program is unique in its diversity as 76% of participants come from communities historically underrepresented in biomedical research, including African Americans, Hispanic/Latinx individuals, Native Hawaiians/Other Pacific Islanders and Asian Americans. This study has the potential to accelerate biomedical research and improve human health by providing a comprehensive understanding of genetic influences on disease risk.


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Confidence

90%

Doubts
  • It is not clear if these DNA variants have been extensively studied before or if they are truly unique.

Sources

84%

The overall score is a weighted number that takes into account conflict of interest, bias, deception and other practices that undermine the credibility of the source. It is calculated as:
(Site Conflicts Of Interest + Author Conflicts Of Interest) / 2.0 * 0.2 + ArticleBiasScore * 0.20 + UniquePointsScore * 0.05 + DeceptionScore * 0.20 + ReadabilityScore * 0.05 + FallacyScore * 0.20

A score that takes into consideration the content for flow, interruptions with ads, and overt search engine optimization techniques that makes the content hard to understand

Genomic data in the All of Us Research Program

Nature Magazine Tuesday, 20 February 2024 00:34
  • Unique Points
    • The All of Us Research Program is a longitudinal cohort study aiming to enroll at least one million individuals across the USA.
    • <4 million of the newly discovered differences in the genetic code are located in areas that may be tied to disease risk.>
    • Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours.
    • <767,000 adults signed up for the program as of this week.>
    • The current 'gold standard' is the UK Biobank which holds genetic variants on 500,001 mostly white individuals.
  • Accuracy
    • 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities.
    • All of Us identified more than 1 billion genetic variants, including over 275 million previously unreported genetic variants.
    • Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry.
    • This diverse dataset will advance the promise of genomic medicine for all.
  • Deception (50%)
    The article is deceptive in several ways. Firstly, the author claims that the All of Us Research Program aims to enroll a diverse group of at least one million individuals across the USA. However, this claim is not supported by any evidence presented in the article and it's unclear how many people have actually been enrolled so far. Secondly, while it's true that 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities, the article does not provide any information on how these groups were recruited or if they had any choice in participating. This raises questions about informed consent and potential coercion. Thirdly, while it's impressive that All of Us identified more than 1billion genetic variants, including over 275 million previously unreported genetic variants, the article does not provide any information on how these variations were validated or if they have been replicated in other studies. This raises concerns about the reliability and accuracy of the data presented. Finally, while it's true that All of Us leverages linkage between genomic data and longitudinal electronic health records to evaluate genetic variants associated with diseases, this information is not relevant to understanding how deceptive practices are present in the article.
    • It's unclear how these groups were recruited or if they had any choice in participating, raising questions about informed consent and potential coercion.
    • The claim that the All of Us Research Program aims to enroll a diverse group of at least one million individuals across the USA is not supported by any evidence presented in the article.
    • The reliability and accuracy of the data presented are called into question because no information on how these variations were validated or replicated is provided.
  • Fallacies (85%)
    The article contains several fallacies. Firstly, the author uses an appeal to authority by stating that identifying genetic variation and cataloguing its contribution to health and disease is a central goal of human health research1,2 without providing any evidence or citation for this claim. Secondly, the author makes a false dilemma by suggesting that there are only two options: either identify genetic variants associated with diseases in diverse populations or not at all. This oversimplifies the complexity of genomic medicine and ignores other factors such as environmental and lifestyle factors that also contribute to health and disease. Thirdly, the author uses inflammatory rhetoric by stating that identifying genetic variation is a key limitation in efforts to build this catalogue without providing any evidence or context for why this is true. Finally, the author makes an informal fallacy by suggesting that there are only two types of individuals: those who are represented in biomedical research and those who are not.
    • The author uses an appeal to authority by stating that identifying genetic variation and cataloguing its contribution to health and disease is a central goal of human health research1,2 without providing any evidence or citation for this claim.
    • The author makes a false dilemma by suggesting that there are only two options: either identify genetic variants associated with diseases in diverse populations or not at all. This oversimplifies the complexity of genomic medicine and ignores other factors such as environmental and lifestyle factors that also contribute to health and disease.
    • The author uses inflammatory rhetoric by stating that identifying genetic variation is a key limitation in efforts to build this catalogue without providing any evidence or context for why this is true.
    • The author makes an informal fallacy by suggesting that there are only two types of individuals: those who are represented in biomedical research and those who are not.
  • Bias (100%)
    None Found At Time Of Publication
  • Site Conflicts Of Interest (100%)
    None Found At Time Of Publication
  • Author Conflicts Of Interest (0%)
    None Found At Time Of Publication

73%

The overall score is a weighted number that takes into account conflict of interest, bias, deception and other practices that undermine the credibility of the source. It is calculated as:
(Site Conflicts Of Interest + Author Conflicts Of Interest) / 2.0 * 0.2 + ArticleBiasScore * 0.20 + UniquePointsScore * 0.05 + DeceptionScore * 0.20 + ReadabilityScore * 0.05 + FallacyScore * 0.20

A score that takes into consideration the content for flow, interruptions with ads, and overt search engine optimization techniques that makes the content hard to understand

275 million new genetic variants found in US study explain why some are more prone to disease than others

Fox News Media Unknown Reuters Tuesday, 20 February 2024 00:36
  • Unique Points
    • Nearly 4 million of the newly discovered differences in the genetic code are located in areas that may be tied to disease risk.
    • The study aims to eventually collect DNA and other health data on 1 million people in hopes of better understanding genetic influences on health and disease.
  • Accuracy
    No Contradictions at Time Of Publication
  • Deception (30%)
    The article is deceptive in several ways. Firstly, the title of the article suggests that a study has found new genetic variants that explain why some are more prone to disease than others. However, this is not entirely accurate as only 275 out of over 1 billion genetic variants discovered by the study were linked to disease risk.
    • The title of the article suggests a direct link between new genetic variants and increased susceptibility to diseases when in fact it's only a small subset that is associated with disease risk.
    • The sentence 'Nearly 4 million of the newly discovered differences in the genetic code are located in areas that may be tied to disease risk, the researchers reported.' implies a direct correlation between these variants and increased susceptibility to diseases when it's not entirely accurate.
  • Fallacies (85%)
    The article contains several examples of informal fallacies. The author uses an appeal to authority by stating that the study was funded by the National Institutes of Health and citing Dr. Josh Denny as a study author and CEO without providing any evidence or context for their expertise in this field.
    • The whole genome sequencing data from a wide range of Americans aims to address the historical lack of diversity in existing genomic datasets by focusing on previously under-represented groups. The U.S. National Institutes of Health-funded
  • Bias (85%)
    The article contains examples of religious bias and monetary bias. The author uses the phrase 'diverse populations' to describe underrepresented groups which implies that they are not diverse by nature but rather due to historical lack of representation in existing genomic datasets. This is a form of religious bias as it assumes that diversity should be present in all populations, regardless of their natural genetic makeup. Additionally, the article mentions funding from the National Institutes of Health (NIH) which implies monetary bias as they are providing financial support for this study.
    • Nearly 90% of genomic studies to date have been done in people of European ancestry, which has led to a narrow understanding of the biology of diseases and slowed the development of drugs and prevention strategies effective in diverse populations.
      • The whole genome sequencing data from a wide range of Americans aims to address the historical lack of diversity in existing genomic datasets by focusing on previously under-represented groups.
      • Site Conflicts Of Interest (50%)
        The article discusses a study that found 275 million new genetic variants in the US. The author of the article is Dr. Josh Denny who has an affiliation with NIH departments and was involved in funding for the All of Us study which also contributed to this research.
        • Dr. Josh Denny, a professor at Harvard Medical School and director of genetics at Brigham Health, led the team that conducted the analysis.
        • Author Conflicts Of Interest (100%)
          None Found At Time Of Publication

        82%

        The overall score is a weighted number that takes into account conflict of interest, bias, deception and other practices that undermine the credibility of the source. It is calculated as:
        (Site Conflicts Of Interest + Author Conflicts Of Interest) / 2.0 * 0.2 + ArticleBiasScore * 0.20 + UniquePointsScore * 0.05 + DeceptionScore * 0.20 + ReadabilityScore * 0.05 + FallacyScore * 0.20

        A score that takes into consideration the content for flow, interruptions with ads, and overt search engine optimization techniques that makes the content hard to understand

        ‘All of Us’ reports half of the genomes it has sequenced are from non-Europeans

        STAT News Megan Molteni Monday, 19 February 2024 16:00
        • Unique Points
          • The National Institutes of Health launched a study to enroll over 1 million participants in an ambitious data-gathering gambit unmatched in its scope and diversity. Since then, Americans from all walks of life have been providing blood, spit, and pee samples for genetic analysis.
          • From those samples, scientists have recovered more than 275 million never-before-seen DNA variants.
        • Accuracy
          No Contradictions at Time Of Publication
        • Deception (100%)
          None Found At Time Of Publication
        • Fallacies (85%)
          The article contains an example of a false dilemma fallacy. The author presents the idea that precision medicine requires diversity in its participants but then states that only people with European ancestry disproportionately drive genetics research. This creates a false choice between having more data from diverse populations or relying on limited data from predominantly white individuals, when in reality there are other options available.
          • The author presents the idea that precision medicine requires diversity in its participants but then states that only people with European ancestry disproportionately drive genetics research. This creates a false choice between having more data from diverse populations or relying on limited data from predominantly white individuals, when in reality there are other options available.
        • Bias (85%)
          The article reports on the release of new genetic data from a study called All of Us. The study aims to address a lack of diversity in genomic datasets that has led to limited understanding of disease biology and undermined precision medicine. The author notes that people with European ancestry account for less than one-quarter of the world's population, but their DNA disproportionately drives genetics research. This is an example of racial bias in science as it assumes that certain groups are more important or valuable to study based on their genetic makeup.
          • The author notes that people with European ancestry account for less than one-quarter of the world's population, but their DNA disproportionately drives genetics research.
          • Site Conflicts Of Interest (50%)
            Megan Molteni has a conflict of interest on the topic of diversity in genomic datasets as she is reporting on an NIH-supported project that aims to increase diversity in such datasets.
            • Author Conflicts Of Interest (50%)
              Megan Molteni has a conflict of interest on the topic of diversity in genomic datasets as she is an author for All of Us research program.

              91%

              The overall score is a weighted number that takes into account conflict of interest, bias, deception and other practices that undermine the credibility of the source. It is calculated as:
              (Site Conflicts Of Interest + Author Conflicts Of Interest) / 2.0 * 0.2 + ArticleBiasScore * 0.20 + UniquePointsScore * 0.05 + DeceptionScore * 0.20 + ReadabilityScore * 0.05 + FallacyScore * 0.20

              A score that takes into consideration the content for flow, interruptions with ads, and overt search engine optimization techniques that makes the content hard to understand

              Genetic risk prediction for ten chronic diseases moves closer to the clinic

              MedicalXpress Science X Tuesday, 20 February 2024 00:44
              • Unique Points
                • The team selected, optimized and validated the tests for 10 common diseases including heart disease.
                • They also calibrated the tests for use in people with non-European ancestries.
                • Broad Clinical Labs at Broad Institute of MIT and Harvard is first author of the new paper.
                • The network wants to know what it means for a person to receive information that says they're at high risk for one of these diseases.
              • Accuracy
                • Most polygenic risk scores have been developed based on genetic data largely from people of European ancestry raising questions about whether the scores are applicable to people of other ancestries.
              • Deception (100%)
                None Found At Time Of Publication
              • Fallacies (100%)
                None Found At Time Of Publication
              • Bias (100%)
                None Found At Time Of Publication
              • Site Conflicts Of Interest (100%)
                None Found At Time Of Publication
              • Author Conflicts Of Interest (50%)
                The author Science X has a conflict of interest on the topics genetic risk prediction and polygenic risk score as they are associated with their affiliation with the Broad Institute of MIT and Harvard. The article also mentions eMERGE network which is another project that Science X is involved in.
                • The study was conducted by researchers at the Broad Institute of MIT and Harvard, where Science X works.

                62%

                The overall score is a weighted number that takes into account conflict of interest, bias, deception and other practices that undermine the credibility of the source. It is calculated as:
                (Site Conflicts Of Interest + Author Conflicts Of Interest) / 2.0 * 0.2 + ArticleBiasScore * 0.20 + UniquePointsScore * 0.05 + DeceptionScore * 0.20 + ReadabilityScore * 0.05 + FallacyScore * 0.20

                A score that takes into consideration the content for flow, interruptions with ads, and overt search engine optimization techniques that makes the content hard to understand

                NIH study uncovers 275MILLION entirely new genetic variants that may explain why some Americans are...

                Daily Mail Luke Andrews Monday, 19 February 2024 18:23
                • Unique Points
                  • More than 275 million entirely new genetic variants have been discovered in people
                  • Nearly 4 million were found in genes linked to a higher risk of cancer, diabetes and heart disease among other conditions.
                  • The current 'gold standard' is the UK Biobank, which holds these figures on 500,001 adults mostly from white backgrounds.
                  • Dr Josh Denny said: Sequencing diverse populations can lead to new drug targets that are relevant to everyone. It can also help uncover disparities that lead to specific treatments for people experiencing higher burdens of disease or different diseases.
                  • The All of Us program was launched in 2018 and by the end of this week had more than 767,000 adults signed up.
                  • It aims to hit 1 million by 2026.
                  • Dr Alicia Martin said: The project is a huge resource, particularly for African American, Hispanic and Latin American genomes.
                  • The researchers found more than a billion genetic variants overall during the research, of which 275million had not previously been recorded.
                  • Many of these new variants were rare and could prove harmless allowing them to rule them out when screening for genes behind certain diseases.
                  • Studies published today using data from the All of Us project highlighted a number of never-before seen genes that could raise someone's risk of suffering from certain diseases.
                  • In one study, researchers found 611 genetic markers that could raise the risk of suffering from type 2 diabetes among nearly 40 percent participants who were minorities.
                  • Results revealed people with European ancestry have about 2.3 percent of their genome made up of pathogenic variants on average while among those with African ancestry, this dropped to 1.6 percent.
                  • Recent studies have already shown how genetic diversity can impact disease risk.
                • Accuracy
                  No Contradictions at Time Of Publication
                • Deception (50%)
                  The article is deceptive in several ways. Firstly, the title claims that the study uncovers new genetic variants that may explain why some Americans are prone to disease. However, this statement is misleading because it implies a causal relationship between these variants and diseases when no such direct link has been established yet. Secondly, the article states that nearly 4 million of the discovered genetic variations were found in genes linked to cancer or diabetes among other conditions. This information is presented as if all these variations are harmful, but this is not entirely accurate because some of them may be benign and therefore do not pose a risk for disease development. Thirdly, the article quotes Dr Josh Denny stating that finding new genotypes in minority populations can help reveal genetic variants that leave some people more at risk from certain diseases or drive the discovery of new drugs to treat these conditions. However, this statement is misleading because it implies that all genetic variations found in minorities are harmful and require further investigation when many of them may be benign and do not pose a significant health risk.
                  • The title claims that the study uncovers new genetic variants that may explain why some Americans are prone to disease. However, this statement is misleading because it implies a causal relationship between these variants and diseases when no such direct link has been established yet.
                • Fallacies (75%)
                  The article contains several examples of informal fallacies. The author uses an appeal to authority by stating that the findings are from a reputable source without providing any evidence for this claim. Additionally, the author makes use of inflammatory rhetoric when describing some genetic variants as being linked to cancer and diabetes.
                  • The current gold standard is the UK Biobank, which holds these figures on 500,000 adults mostly from white backgrounds.
                • Bias (100%)
                  None Found At Time Of Publication
                • Site Conflicts Of Interest (0%)
                  Luke Andrews has a conflict of interest on the topics of genetic variants and disease risk assessment tools as he is an employee at Massachusetts General Hospital in Boston. He also has a personal relationship with Dr Josh Denny who was involved in the study.
                  • Author Conflicts Of Interest (0%)
                    Luke Andrews has a conflict of interest on the topics of genetic variants and disease risk assessment tools as he is an author for both. He also has a financial tie to Massachusetts General Hospital in Boston where the study was conducted.