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The role of the clinician in the multi‐omics era: are you ready?

Overview of attention for article published in Journal of Inherited Metabolic Disease, January 2018
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Title
The role of the clinician in the multi‐omics era: are you ready?
Published in
Journal of Inherited Metabolic Disease, January 2018
DOI 10.1007/s10545-017-0128-1
Pubmed ID
Authors

Clara D. M. van Karnebeek, Saskia B. Wortmann, Maja Tarailo‐Graovac, Mirjam Langeveld, Carlos R. Ferreira, Jiddeke M. van de Kamp, Carla E. Hollak, Wyeth W. Wasserman, Hans R. Waterham, Ron A. Wevers, Tobias B. Haack, Ronald J.A. Wanders, Kym M. Boycott

Abstract

Since Garrod's first description of alkaptonuria in 1902, and newborn screening for phenylketonuria introduced in the 1960s, P4 medicine (preventive, predictive, personalized, and participatory) has been a reality for the clinician serving patients with inherited metabolic diseases. The era of high-throughput technologies promises to accelerate its scale dramatically. Genomics, transcriptomics, epigenomics, proteomics, glycomics, metabolomics, and lipidomics offer an amazing opportunity for holistic investigation and contextual pathophysiologic understanding of inherited metabolic diseases for precise diagnosis and tailored treatment. While each of the -omics technologies is important to systems biology, some are more mature than others. Exome sequencing is emerging as a reimbursed test in clinics around the world, and untargeted metabolomics has the potential to serve as a single biochemical testing platform. The challenge lies in the integration and cautious interpretation of these big data, with translation into clinically meaningful information and/or action for our patients. A daunting but exciting task for the clinician; we provide clinical cases to illustrate the importance of his/her role as the connector between physicians, laboratory experts and researchers in the basic, computer, and clinical sciences. Open collaborations, data sharing, functional assays, and model organisms play a key role in the validation of -omics discoveries. Having all the right expertise at the table when discussing the diagnostic approach and individualized management plan according to the information yielded by -omics investigations (e.g., actionable mutations, novel therapeutic interventions), is the stepping stone of P4 medicine. Patient participation and the adjustment of the medical team's plan to his/her and the family's wishes most certainly is the capstone. Are you ready?

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X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 139 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 17%
Student > Ph. D. Student 21 15%
Student > Doctoral Student 15 11%
Student > Master 11 8%
Student > Bachelor 11 8%
Other 30 22%
Unknown 28 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 32 23%
Medicine and Dentistry 28 20%
Agricultural and Biological Sciences 14 10%
Unspecified 5 4%
Chemistry 5 4%
Other 21 15%
Unknown 34 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 March 2020.
All research outputs
#6,305,626
of 23,018,998 outputs
Outputs from Journal of Inherited Metabolic Disease
#533
of 1,869 outputs
Outputs of similar age
#129,411
of 441,019 outputs
Outputs of similar age from Journal of Inherited Metabolic Disease
#7
of 33 outputs
Altmetric has tracked 23,018,998 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,869 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 71% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 441,019 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.