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Health Profiles of Mosaic Versus Non-mosaic FMR1 Premutation Carrier Mothers of Children With Fragile X Syndrome

Overview of attention for article published in Frontiers in Genetics, May 2018
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  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Health Profiles of Mosaic Versus Non-mosaic FMR1 Premutation Carrier Mothers of Children With Fragile X Syndrome
Published in
Frontiers in Genetics, May 2018
DOI 10.3389/fgene.2018.00173
Pubmed ID
Authors

Marsha R. Mailick, Arezoo Movaghar, Jinkuk Hong, Jan S. Greenberg, Leann S. DaWalt, Lili Zhou, Jonathan Jackson, Paul J. Rathouz, Mei W. Baker, Murray Brilliant, David Page, Elizabeth Berry-Kravis

Abstract

The FMR1 premutation is of increasing interest to the FXS community, as questions about a primary premutation phenotype warrant research attention. 100 FMR1 premutation carrier mothers (mean age = 58; 67-138 CGG repeats) of adults with fragile X syndrome were studied with respect to their physical and mental health, motor, and neurocognitive characteristics. We explored the correlates of CGG repeat mosaicism in women with expanded alleles. Mothers provided buccal swabs from which DNA was extracted and the FMR1 CGG genotyping was performed (Amplidex Kit, Asuragen). Mothers were categorized into three groups: Group 1: premutation non-mosaic (n = 45); Group 2: premutation mosaic (n = 41), and Group 3: premutation/full mutation mosaic (n = 14). Group 2 mothers had at least two populations of cells with different allele sizes in the premutation range besides their major expanded allele. Group 3 mothers had a very small population of cells in the full mutation range (>200 CGGs) in addition to one or multiple populations of cells with different allele sizes in the premutation range. Machine learning (random forest) was used to identify symptoms and conditions that correctly classified mothers with respect to mosaicism; follow-up comparisons were made to characterize the three groups. In categorizing mosaicism, the random forest yielded significantly better classification than random classification, with overall area under the receiver operating characteristic curve (AUROC) of 0.737. Among the most important symptoms and conditions that contributed to the classification were anxiety, menopause symptoms, executive functioning limitations, and difficulty walking several blocks, with the women who had full mutation mosaicism (Group 3) unexpectedly having better health. Although only 14 premutation carrier mothers in the present sample also had a small population of full mutation cells, their profile of comparatively better health, mental health, and executive functioning was unexpected. This preliminary finding should prompt additional research on larger numbers of participants with more extensive phenotyping to confirm the clinical correlates of low-level full mutation mosaicism in premutation carriers and to probe possible mechanisms.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 15%
Researcher 8 15%
Student > Ph. D. Student 8 15%
Student > Doctoral Student 6 11%
Professor 4 7%
Other 5 9%
Unknown 16 29%
Readers by discipline Count As %
Psychology 11 20%
Biochemistry, Genetics and Molecular Biology 5 9%
Neuroscience 5 9%
Social Sciences 4 7%
Nursing and Health Professions 2 4%
Other 9 16%
Unknown 19 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 20 May 2018.
All research outputs
#5,927,400
of 23,055,429 outputs
Outputs from Frontiers in Genetics
#1,695
of 12,106 outputs
Outputs of similar age
#103,238
of 327,731 outputs
Outputs of similar age from Frontiers in Genetics
#28
of 126 outputs
Altmetric has tracked 23,055,429 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 12,106 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 85% 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 327,731 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 68% of its contemporaries.
We're also able to compare this research output to 126 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.