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Sökning: onr:"swepub:oai:gup.ub.gu.se/267380" > Genetic validation ...

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FältnamnIndikatorerMetadata
00005670naa a2200733 4500
001oai:gup.ub.gu.se/267380
003SwePub
008240410s2018 | |||||||||||000 ||eng|
009oai:prod.swepub.kib.ki.se:138222316
0247 a https://gup.ub.gu.se/publication/2673802 URI
0247 a https://doi.org/10.1038/s41398-018-0133-72 DOI
0247 a http://kipublications.ki.se/Default.aspx?queryparsed=id:1382223162 URI
040 a (SwePub)gud (SwePub)ki
041 a eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Chen, C. Y.4 aut
2451 0a Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records
264 c 2018-04-18
264 1b Springer Science and Business Media LLC,c 2018
520 a Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. Am J Psychiatry 172:363-372, 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3330 BD cases and 3952 controls of European ancestry were used to estimate SNP-based heritability (h 2 g) and genetic correlation (r g) between EHR-based phenotype definitions and traditionally ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and three rule-based algorithms using codified EHR with decreasing levels of stringency-"coded-strict", "coded-broad", and "coded-broad based on a single clinical encounter" (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1968 coded-strict, 2581 coded-broad, 408 coded-broad-SV BD cases, and 3 952 controls. The estimated h 2 g were 0.24 (p = 0.015), 0.09 (p = 0.064), 0.13 (p = 0.003), 0.00 (p = 0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h 2 g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h 2 g) was 0.12 (p = 0.004). These h 2 g were lower or similar to the h 2 g observed by the ICCBD + PGCBD (0.23, p = 3.17E-80, total N = 33,181). However, the r g between ICCBD + PGCBD and the EHR-based cases were high for 95-NLP (0.66, p = 3.69 × 10-5), coded-strict (1.00, p = 2.40 × 10-4), and coded-broad (0.74, p = 8.11 × 10-7). The r g between EHR-based BD definitions ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Psykiatri0 (SwePub)302152 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Psychiatry0 (SwePub)302152 hsv//eng
653 a Article
653 a automation
653 a bipolar disorder
653 a case control study
653 a controlled study
653 a electronic health record
653 a genetic algorithm
653 a genetic correlation
653 a genetic screening
653 a genotype
653 a health care system
653 a heritability
653 a human
653 a major clinical study
653 a phenotype
653 a scoring system
653 a single nucleotide polymorphism
653 a validation process
7001 a Lee, P. H.4 aut
7001 a Castro, V. M.4 aut
7001 a Minnier, J.4 aut
7001 a Charney, A. W.4 aut
7001 a Stahl, E. A.4 aut
7001 a Ruderfer, D. M.4 aut
7001 a Murphy, S. N.4 aut
7001 a Gainer, V.4 aut
7001 a Cai, T.4 aut
7001 a Jones, I.4 aut
7001 a Pato, C. N.4 aut
7001 a Pato, M. T.4 aut
7001 a Landén, Mikael,d 1966u Karolinska Institutet,Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för psykiatri och neurokemi,Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry4 aut0 (Swepub:gu)xlandt
7001 a Sklar, P.4 aut
7001 a Perlis, R. H.4 aut
7001 a Smoller, J. W.4 aut
7102 a Göteborgs universitetb Institutionen för neurovetenskap och fysiologi, sektionen för psykiatri och neurokemi4 org
7730 t Translational Psychiatryd : Springer Science and Business Media LLCg 8:1, s. 1-8q 8:1<1-8x 2158-3188
8564 u https://www.nature.com/articles/s41398-018-0133-7.pdf
8564 8u https://gup.ub.gu.se/publication/267380
8564 8u https://doi.org/10.1038/s41398-018-0133-7
8564 8u http://kipublications.ki.se/Default.aspx?queryparsed=id:138222316

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