Publications by authors named "Erika M Kvikstad"

Article Synopsis
  • Whole genome sequencing (WGS) is being increasingly used to diagnose rare diseases, but traditional methods often have low diagnostic yields, typically 25-30%.
  • In a study involving 122 rare disease patients and their relatives, a comprehensive bioinformatics approach led to a diagnostic yield of 35%, with 39% solved when including novel gene candidates.
  • The study also identified several novel genes, expanded the phenotypic understanding of existing conditions, and resulted in critical changes to clinical diagnoses and treatments for some patients.
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Article Synopsis
  • The Pharma Proteomics Project is a large-scale research initiative analyzing blood protein profiles from over 54,000 UK Biobank participants to understand links between genetics and health.
  • The project identifies significant genetic associations with proteins, revealing many novel interactions and highlighting ancestry-specific variations, along with insights into disease mechanisms and potential drug targets.
  • By making their findings publicly accessible, the consortium aims to advance research in biomarker development and therapeutic strategies, enhancing our understanding of how genetic factors influence health outcomes.
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Purpose: The translation of genome sequencing into routine health care has been slow, partly because of concerns about affordability. The aspirational cost of sequencing a genome is $1000, but there is little evidence to support this estimate. We estimate the cost of using genome sequencing in routine clinical care in patients with cancer or rare diseases.

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Next-generation sequencing (NGS) efforts have established catalogs of mutations relevant to cancer development. However, the clinical utility of this information remains largely unexplored. Here, we present the results of the first eight patients recruited into a clinical whole-genome sequencing (WGS) program in the United Kingdom.

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Background: Transposable elements (TEs) are mobile genetic sequences that randomly propagate within their host's genome. This mobility has the potential to affect gene transcription and cause disease. However, TEs are technically challenging to identify, which complicates efforts to assess the impact of TE insertions on disease.

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Elucidating the mechanisms of mutation accumulation and fixation is critical to understand the nature of genetic variation and its contribution to genome evolution. Of particular interest is the effect of insertions and deletions (indels) on the evolution of genome landscapes. Recent population-scaled sequencing efforts provide unprecedented data for analyzing the relative impact of selection versus nonadaptive forces operating on indels.

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The densities of transposable elements (TEs) in the human genome display substantial variation both within individual chromosomes and among chromosome types (autosomes and the two sex chromosomes). Finding an explanation for this variability has been challenging, especially in light of genome landscapes unique to the sex chromosomes. Here, using a multiple regression framework, we investigate primate Alu and L1 densities shaped by regional genome features and location on a particular chromosome type.

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Recent studies have revealed that insertions and deletions (indels) are more different in their formation than previously assumed. What remains enigmatic is how the local DNA sequence context contributes to these differences. To investigate the relative impact of various molecular mechanisms to indel formation, we analyzed sequence contexts of indels in the non protein- or RNA-coding, nonrepetitive (NCNR) portion of the human genome.

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Insertions and deletions (indels) cause numerous genetic diseases and lead to pronounced evolutionary differences among genomes. The macaque sequences provide an opportunity to gain insights into the mechanisms generating these mutations on a genome-wide scale by establishing the polarity of indels occurring in the human lineage since its divergence from the chimpanzee. Here we apply novel regression techniques and multiscale analyses to demonstrate an extensive regional indel rate variation stemming from local fluctuations in divergence, GC content, male and female recombination rates, proximity to telomeres, and other genomic factors.

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