Human genetics and public health are increasingly intertwined disciplines. Historical breakthroughs in genetics have provided unprecedented insights into the biological basis of health and disease, leading to modernized public health strategies (Mikail, 2008). As our understanding of the human genome expands, so does the potential to prevent disease. Modern genomics study has led to the creation of several government agencies who regulate and fund the advancement of the field. Since the confirmation of DNA as genetic material in 1952, genetics and genomics have advanced tremendously to the point where we have mapped the entire human genome. Using the knowledge gained from these pioneers, we have gained an understanding of various mutations and how they contribute to the field of public health.

The timeline for understanding the genetic basis of life and its implications for public health has been marked by several pivotal discoveries. A foundational moment was the confirmation of DNA as the genetic material. In 1952, Alfred Hershey and Martha Chase conclusively demonstrated that DNA carried the hereditary information (Cohn, Scherer, & Hamosh, 2024). This was built upon earlier work by Oswald Avery and colleagues. Prior to these studies, it was believed that genetic material was carried through protein, due to the vast number of possible protein configurations.

Shortly thereafter, Rosalind Franklin’s X-ray diffraction work provided imaging of the DNA molecule. These images were instrumental for James Watson and Francis Crick, who in 1953 proposed the double helical structure of DNA (Cohn, Scherer, & Hamosh, 2024). This discovery was revolutionary, as the structure suggested mechanisms for DNA replication and information storage. This would later explain how genetic traits are passed down and how alterations could lead to disease. Molecular understanding became the foundation for future genetic research and its application to health.

The Human Genome Project was launched in 1990 and completed in 2003. The project was a giant leap forward in genetics. It was an international effort which successfully mapped and sequenced nearly all the genes of the human genome (Mikail, 2008). The Human Genome Project provided an invaluable reference sequence, accelerating gene discovery for monogenic and complex diseases. Its public health impact includes enabling the development of more comprehensive newborn screening panels, carrier screening, and susceptibility testing for common diseases, laying the basis for predictive and preventive medicine (Mikail, 2008).

Modern advancements, such as whole genome sequencing (WGS) and other next-generation sequencing (NGS) technologies, have reduced the costs and increased the speed of sequencing. This has revolutionized diagnostics for genetic disorders, improved our understanding of cancer genomics, and enhanced public health surveillance through rapid pathogen genome sequencing (Katsanis & Katsanis, 2013).

Translating genomic discoveries into public health benefits is supported and guided by state and federal government agencies. The National Institutes of Health (NIH) is a primary driver, funding a vast portfolio of clinical research in genetics and genomics. Within the NIH, institutes like the National Human Genome Research Institute (NHGRI) spearhead major initiatives, including the HGP and ongoing research into the genomic basis of disease (Mikail, 2008, p. 17).

The Centers for Disease Control and Prevention (CDC) also plays a role through its National Office of Public Health Genomics (NOPHG), formerly the Office of Genomics and Disease Prevention (Mikail, 2008, p. 17). The NOPHG focuses on integrating genomics into public health practice. CDC initiatives include the Family History Public Health Initiative, which developed and promoted tools to facilitate the use of family history for primary and secondary prevention of common diseases with genetic components (Mikail, 2008, p. 25). Another important program was the Evaluation of Genomic Applications in Practice and Prevention (EGAPP), which established a systematic, evidence-based process for assessing the validity and utility of new genetic tests for clinical and public health applications.

Addressing the societal impact of genomics is also a governmental priority. The Ethical, Legal, and Social Implications (ELSI) Research Program, primarily funded by the NHGRI, supports research into complex issues arising from genomic advancements, such as genetic privacy, discrimination, and equitable access to genomic medicine (NIH, 2025). Another important initiative, the CDC’s Microbial Sequencing Center, developed methods to swiftly sequence genomes of harmful microbes, aiding in biodefense and the control of infectious disease outbreaks (Mikail, 2008, p. 25). State public health departments typically implement federal guidelines, manage newborn screening programs, conduct disease surveillance that may incorporate genetic data, and support access to genetic services.

The use of race and ethnicity in public health genetics is complex and debated. Race and ethnicity are primarily social and cultural constructs, not always biological or genetic categories. Patterns of genetic variation can differ on average between groups with shared ancestry due to population history (West, Blacksher, & Burke, 2017).

A positive aspect of the use of race and ethnicity is the ability to identify populations that may have a higher prevalence of specific genetic variants associated with disease risk. For example, cystic fibrosis is most common in individuals of Northern European descent due to higher carrier frequencies of specific CFTR mutations in these populations, while Tay-Sachs disease is more prevalent among individuals of Ashkenazi Jewish descent (Mikail, 2008). Recognizing these associations could help target screening programs or public health initiatives to populations that benefit most, improving resource allocation and early detection (West, Blacksher, & Burke, 2017).

A major issue that we are currently facing is the significant overrepresentation of individuals of European ancestry in genomic research databases (West, Blacksher, & Burke, 2017).This bias means that genetic tests and risk prediction models, such as polygenic risk scores, developed using this data often have reduced accuracy and utility when applied to individuals from other ancestral backgrounds (West, Blacksher, & Burke, 2017). Using race or ethnicity as a proxy for genetic risk can also lead to the misinterpretation of these categories as genetically definitive. This could reinforce harmful notions and stereotypes of biological race and potentially lead to stigmatization or overlooking at-risk individuals in majority populations (Macias-Konstantopoulos, et al., 2023). For example, while some CFTR mutations are common in Caucasians, different mutations cause cystic fibrosis in other populations. This could mean that a test panel designed primarily for one group might miss affected individuals in another. There is also considerable genetic diversity within any racial or ethnic group, and significant overlap between groups, making race a poor predictor of individual genetic makeup or disease risk (Macias-Konstantopoulos, et al., 2023).

Mutations provide genetic variation, good or bad, in populations (Dubei, 2022). They can be broadly categorized based on the cell type affected. Somatic mutations occur in non-reproductive cells and are not passed on to offspring. They can contribute to an individual’s aging or cancer development. Germline mutations occur in egg or sperm cells and can be inherited by offspring, affecting every cell in their body and potentially leading to hereditary diseases (Dubei, 2022).

Mutations can range from changes in a single DNA base to alterations involving larger DNA segments. Common types of mutations include missense mutations, wherein a single nucleotide change creates a codon that codes for a different amino acid. This may or may not have a significant effect on protein function. A nonsense mutation occurs when a single nucleotide change codes for a premature stop codon. This would lead to a truncated, often non-functional protein (Dubei, 2022). Frameshift mutations are caused by insertions or deletions of nucleotides in multiples of three. This type of mutation alters the gene’s reading frame, which can lead to a completely different amino acid sequence downstream (Dubei, 2022). Functionally, mutations can lead to a loss-of-function, where the gene product has reduced or no activity, or a gain-of-function, where the gene product gains a new or enhanced abnormal activity (Dubei, 2022).

In population genetics, mutations introduce new alleles into a population’s gene pool. Population genetics studies how the frequencies of these alleles and genotypes can change over generations due to evolutionary forces (Dubei, 2022). Studying mutation rates and the distribution of specific mutations within and between populations is the basis of understanding human evolutionary history and the genetic basis of trait variation (Mikail, 2008).

The historical timeline from fundamental discoveries like DNA structure to human genome mapping and the advent of rapid sequencing technologies has helped shape the field of public health. Government agencies play an important role in fostering research, ensuring ethical application, and translating genomic knowledge into tangible health benefits for populations. However, the equitable use of genetic information across diverse racial and ethnic groups is still difficult due to prohibitive cost and disinterest in certain countries and populations. The ongoing integration of genetics into public health promises further advancements but requires continuous attention to scientific validity, clinical utility, and equitable application.

References

Cohn, R. D., Scherer, S. W., & Hamosh, A. (2024). Genetics and Genomkics in Medicine (Vol. Ninth Edition). Philadelphia, Pennsylvania: Elsevier.

Dubei, W. (2022). Review on Mutations and its Determinations. Journal of Molecular and Genetic, https://www.hilarispublisher.com/open-access/review-on-mutations-and-its-determinations.pdf.

Katsanis, S. H., & Katsanis, N. (2013). Molecular genetic testing and the future of clinical genomics. Nature Reviews Genetics, 14, 415-426, https://doi.org/10.1038/nrg3493.

Macias-Konstantopoulos, W. L., Collins, K. A., Diaz, R., Duber, H. C., Edwards, C. D., Hsu, A. P., . . . Sachs, C. J. (2023). Race, Healthcare, and Health Disparities: A Critical Review and Recommendations for Advancing Health Equity. The western journal of emergency medicine, 24(5), 906-918. https://doi.org/10.5811/westjem.58408.

Mikail, C. N. (2008). Public Health Genomics. San Francisco: Wiley.

NIH. (2025, 05 18). Ethical, Legal and Social Implications Research Program. Retrieved from Genome.gov: https://www.genome.gov/Funded-Programs-Projects/ELSI-Research-Program-ethical-legal-social-implications

West, K. M., Blacksher, E., & Burke, W. (2017). Genomics, Health Disparities, and Missed Opportunities for the Nation’s Research Agenda. JAMA, 317(18), 1831–1832. https://doi.org/10.1001/jama.2017.3096.