A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Data from electronic healthcare records expand our understanding of X-linked genetic diseases. | LitMetric

AI Article Synopsis

  • The study analyzed electronic health records (EHR) to examine X-linked (XL) disorders in both males and females at Vanderbilt University over a 20-year period, involving 477 males and 203 females diagnosed with 108 different XL disorders.
  • It revealed significant variations in the female-to-male (F/M) ratios for XL disorders, with some XL recessive disorders observed in women that were previously documented only in men.
  • The findings suggested that traditional Mendelian predictions about gender ratios in XL disorders may not accurately reflect real-world data, indicating a need for further research to confirm these insights in larger EHR cohorts.

Article Abstract

Disease specific cohort studies have reported details on X linked (XL) disorders affecting females. We investigated the spectrum and penetrance of XL disorders seen in electronic health records (EHR). We generated a cohort of individuals diagnosed with XL disorders at Vanderbilt University Medical Center over 20 years. Our cohort included 477 males and 203 females diagnosed with 108 different XL genetic disorders. We found large differences between the female/male (F/M) ratios for various XL disorders regardless of their OMIM annotated mode of inheritance. We identified four XL recessive disorders affecting women previously only described in men. Biomarkers for XL disease had unique gender-specific patterns differing between modes of inheritance. EHRs provide large cohorts of XL genetic disorders that give new insights compared to the literature. Differences in the F/M ratios and biomarkers of XL disorders observed likely result from disease specific and sex dependent penetrance. We conclude that observed gender ratios associated with specific XL disorders may be more useful than those predicted by Mendelian genetics provided by OMIM. Our findings of a gender specific penetrance and severity for XL disorders show unexpected differences from Mendelian predictions. Further work is required to validate our findings in larger combined EHR cohorts.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11181165PMC
http://dx.doi.org/10.1002/ajmg.a.63527DOI Listing

Publication Analysis

Top Keywords

disorders
10
disease specific
8
genetic disorders
8
f/m ratios
8
data electronic
4
electronic healthcare
4
healthcare records
4
records expand
4
expand understanding
4
understanding x-linked
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!