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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Related Experiment Video

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Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management
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Diverse Genomes, Shared Health: Insights from a Health System Biobank.

Roni Haas1,2,3,4, Michael P Margolis1,5,6, Angela Wei1,7,8,9

  • 1Department of Human Genetics, University of California, Los Angeles, USA.

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Summary

Diverse biobanks are crucial for precision medicine, but often lack ancestral diversity. This study used a diverse biobank to identify novel genetic associations and improve disease prediction across various populations.

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Area of Science:

  • Genomics and Precision Medicine
  • Population Genetics
  • Health Disparities

Background:

  • Precision medicine relies on genetic profiling and electronic health records, but limited ancestral diversity hinders discovery and generalizability.
  • Hospital biobanks often lack representation from non-European populations, creating gaps in understanding disease prevalence and genetic risk.

Purpose of the Study:

  • To leverage a diverse biobank (UCLA ATLAS Community Health Initiative) to investigate disease prevalence and genetic risk across diverse ancestry groups.
  • To identify novel genetic associations and evaluate the performance of polygenic scores across different ancestries.
  • To address biases in curated clinical variants and discover new gene-disease associations in underrepresented populations.

Main Methods:

  • Analysis of clinical and genetic data from 93,937 individuals, including whole-exome sequencing (WES) for 61,797 participants.
  • Examination of disease prevalence and genetic risk across five continental and 36 fine-scale ancestry groups.
  • Utilizing computationally predicted deleterious variants to mitigate bias in curated clinical variant databases.

Main Results:

  • Novel associations identified, including *STARD7* with asthma in Mexican Americans and *FN3K* with intestinal disaccharidase deficiency.
  • Polygenic scores (PGS) showed diminished predictive power for common diseases in non-European populations.
  • Identified new gene-disease associations, such as *EXOC1L* with blood glucose in East Asians, and *PTPRU* as a modulator of semaglutide's weight loss effects.

Conclusions:

  • Ancestral diversity in biobanks is essential for advancing precision health and ensuring equitable discovery across populations.
  • Addressing biases in genetic databases and incorporating diverse data are critical for accurate disease prediction and treatment.
  • The study highlights the need for inclusive research to fully realize the potential of precision medicine for all individuals.