Linked Life Data

11121189

Source:http://linkedlifedata.com/resource/pubmed/id/11121189

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2000-12-21
pubmed:abstractText
Comorbidity, the co-occurrence of disorders, is frequently observed to occur at higher rates in clinically ascertained samples than in population-based samples. An explanation for this finding is that subjects suffering from multiple illnesses are more likely to seek medical care and receive a diagnostic evaluation. We refer to the component of the comorbidity between illnesses due to such ascertainment bias as "spurious comorbidity." When spurious comorbidity is present, an apparent association between a candidate locus and the phenotype of interest may actually be attributable to an association between the locus and a comorbid phenotype. This phenomenon, which we call "spurious comorbidity bias," could thus produce misleading association findings. In this article, we describe this phenomenon and demonstrate that it may produce marked bias in the conclusions of family-based association studies. Because of the extremely high rates of comorbidity among psychiatric disorders in clinical samples, this problem may be particularly salient for genetic studies of neuropsychiatric disorders. We conclude that ascertainment bias may contribute to the frequent difficulty in replicating candidate gene study findings in psychiatry. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:817-822, 2000.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0148-7299
pubmed:author
pubmed:copyrightInfo
Copyright 2000 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:day
4
pubmed:volume
96
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
817-22
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Implications of comorbidity and ascertainment bias for identifying disease genes.
pubmed:affiliation
Harvard School of Public Health, Boston, Massachusetts, USA. jordan_smoller@hms.harvard.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.