To understand disease relationships in terms of their genetic mechanisms, it is important to study the common genetic basis among different diseases. Although discoveries on pleiotropic genes related to multiple diseases abound, methods flexibly applicable to various types of datasets generated from different studies or experiments are needed to gain big pictures on the genetic relationships among a large number of diseases. We develop a set of genetic similarity measures to gauge the genetic overlap between diseases, as well as several estimators of the number of overlapping disease genes between diseases. These methods are based on ranked gene lists so that they could be flexibly applied to different types of data. We first investigate the performance of the genetic similarity measure for evaluating the similarity between human diseases in simulation studies. Then we apply the method to diseases in the OMIM database. We show that our proposed genetic measure achieves superior performance in explaining phenotype similarities between diseases compared to simpler methods. Furthermore, we identified common genes underlying the genetic overlap between disease pairs. With an example of five vision-related diseases, we demonstrate how our methods can provide insights into the relationships among diseases based on their shared genetic mechanisms.
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References
1.
AdlerP., KoldeR., KullM., et al.2009. Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods. Genome Biol., 10, R139.
2.
AertsS., LambrechtsD., MaityS., et al.2006. Gene prioritization through genomic data fusion. Nat. Biotechnol, 24, 537–544.
3.
AntoshM., FoxD., CooperL.N., et al.2013. CORaL: comparison of ranked lists for analysis of gene expression data. J. Comput. Biol., 20, 433–443.
4.
BhattacherjeeV., HornK.H., SinghS., et al.2009. CBP/p300 and associated transcriptional co-activators exhibit distinct expression patterns during murine craniofacial and neural tube development. The Int. J. Dev. Biol., 53, 1097–1104.
5.
BlonigenD.M., HicksB.M., KruegerR.F., et al.2005. Psychopathic personality traits: heritability and genetic overlap with internalizing and externalizing psychopathology. Psychol. Medicine, 35, 637–648.
6.
BoulesteixA.-L., and SlawskiM.2009. Stability and aggregation of ranked gene lists. Briefings Bioinforma., 10, 556–568.
7.
ChenC., and KarlinS.2007. r-Scan statistics of a poisson process with events transformed by duplications, deletions, and displacements. Adv. Appl. Probab., 39, 799–825.
8.
CotsapasC., VoightB.F., RossinE., et al.2011. Pervasive sharing of genetic effects in autoimmune disease. PLoS Genet., 7, e1002254.
9.
DanoyP., PryceK., HadlerJ., et al.2010. Association of variants at 1q32 and STAT3 with ankylosing spondylitis suggests genetic overlap with crohn's disease. PLoS Genet., 6, e1001195.
10.
DengX., XuJ., and WangC.2008. Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists. BMC Bioinforma., 9, S14.
11.
DighieroP., BalayreS., GicquelJ.-J., et al.2004. Corneal recurrent erosions and mutations in the gene COL7A1. ARVO Meet. Abstr., 45, 1510.
12.
EllinghausD., EllinghausE., NairR.P., et al.2012. Combined analysis of genome-wide association studies for crohn disease and psoriasis identifies seven shared susceptibility loci. The Am. J. Hum. Genet., 90, 636–647.
13.
EwensW.J., EwensW.J., and GrantG.2006. Statistical Methods in Bioinformatics: An Introduction. Springer, New York.
14.
EyreS., HinksA., BowesJ., et al.2010. Overlapping genetic susceptibility variants between three autoimmune disorders: rheumatoid arthritis, type 1 diabetes and coeliac disease. Arthritis Res. & Ther., 12, R175.
15.
FuryW., BatliwallaF., GregersenP., et al.2006. Overlapping probabilities of top ranking gene lists, hypergeometric distribution, and stringency of gene selection criterion, 5531–5534. In 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006.
16.
HindorffL.A., SethupathyP., JunkinsH.A., et al.2009. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. United States Am., 106, 9362–9367.
17.
JawaheerD., SeldinM.F., AmosC.I., et al.2001. A genomewide screen in multiplex rheumatoid arthritis families suggests genetic overlap with other autoimmune diseases. Am. J. Hum. Genet., 68, 927–936.
18.
JurmanG., RiccadonnaS., VisintainerR., et al.2012. Algebraic comparison of partial lists in bioinformatics. PLoS ONE, 7, e36540.
19.
KalariaR.N. and BallardC.1999. Overlap between pathology of alzheimer disease and vascular dementia. Alzheimer Dis. Assoc. Disord., 13, S115–S123.
20.
KarlinS., and BrendelV.1992. Chance and statistical significance in protein and DNA sequence analysis. Sci., 257, 39–49.
21.
KarlinS., and ChenC.2004. r-Scan extremal statistics of inhomogeneous poisson processes. Lect. Notes-Monograph Ser., 45, 287–290.
22.
LageK., KarlbergE.O., StrlingZ.M., et al.2007. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat. Biotechnol., 25, 309–316.
23.
LinS.2010. Space oriented rank-based data integration. Stat. Appl. Genet. Mol. Biol. [Epub ahead of print]; doi: 10.2202/1544-6115.1534
24.
LinS., and DingJ.2009. Integration of ranked lists via cross entropy monte carlo with applications to mRNA and microRNA studies. Biom., 65, 918.
25.
LinghuB., SnitkinE.S., HuZ., et al.2009. Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network. Genome Biol., 10, R91.
26.
LottazC., YangX., ScheidS., et al.2006. OrderedLista bioconductor package for detecting similarity in ordered gene lists. Bioinforma., 22, 2315–2316.
27.
LuW., GuzmanA.R., YangW., et al.2010. Genes encoding critical transcriptional activators for murine neural tube development and human spina bifida: a case-control study. BMC Med. Genet., 11, 141.
28.
NatarajanL., PuM., and MesserK.2012. Statistical tests for the intersection of independent lists of genes: Sensitivity, FDR, and type I error control. The Annals Appl. Stat., 6, 521–541.
29.
NiS., and VingronM.2012. R2KS: a novel measure for comparing gene expression based on ranked gene lists. J. Comput. Biol., 19, 766–775.
30.
PihurV., DattaS., and DattaS.2009. RankAggreg, an r package for weighted rank aggregation. BMC Bioinforma., 10, 62.
31.
PlaisierS.B., TaschereauR., WongJ.A., et al.2010. Rankrank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures. Nucleic Acids Res., 38, e169–e169.
32.
RobinsonP.N., KohlerS., BauerS., et al.2008. The human phenotype ontology: A tool for annotating and analyzing human hereditary disease. Am. J. Hum. Genet., 83, 610–615.
33.
RoiderH.G., MankeT., O'KeeffeS., et al.2009. PASTAA: identifying transcription factors associated with sets of co-regulated genes. Bioinforma., 25, 435–442.
34.
RzhetskyA., WajngurtD., ParkN., et al.2007. Probing genetic overlap among complex human phenotypes. Proc. Natl. Acad. Sci., 104, 11694–11699.
35.
ScherrerJ.F., XianH., BucholzK.K., et al.2003. A twin study of depression symptoms, hypertension, and heart disease in middle-aged men. Psychosom. Medicine, 65, 548–557.
36.
SchultzJ.M., BhattiR., MadeoA.C., et al.2011. Allelic hierarchy of CDH23 mutations causing non-syndromic deafness DFNB12 or usher syndrome USH1D in compound heterozygotes. J. Med. Genet., 48(11):767–775.
37.
ShaikhibrahimZ., LindstrotA., BuettnerR., et al.2011. Analysis of laser-microdissected prostate cancer tissues reveals potential tumor markers. Int. J. Mol. Medicine, 28, 605–611.
38.
SivakumaranS., AgakovF., TheodoratouE., et al.2011. Abundant pleiotropy in human complex diseases and traits. The Am. J. Hum. Genet., 89, 607–618.
39.
SmithA.D., SumazinP., DasD., et al.2005. Mining ChIP-chip data for transcription factor and cofactor binding sites. Bioinforma., 21, i403–i412.
40.
SmythD.J., PlagnolV., WalkerN.M., et al.2008. Shared and distinct genetic variants in type 1 diabetes and celiac disease. New Engl. J. Medicine, 359, 2767–2777.
41.
SubramanianA., TamayoP., MoothaV.K., et al.2005. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. United States Am., 102, 15545–15550.
42.
SuthramS., DudleyJ.T., ChiangA.P., et al.2010. Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. PLoS Comput. Biol., 6, e1000662.
43.
ToulopoulouT., PicchioniM., RijsdijkF., et al.2007. Substantial genetic overlap between neurocognition and schizophrenia: Genetic modeling in twin samples. Arch. Gen. Psychiatry, 64, 1348.
44.
TrancheventL.-C., BarriotR., YuS., et al.2008. Endeavour update: a web resource for gene prioritization in multiple species. Nucleic Acids Res., 36, W377–W384.
45.
van DrielM.A., BruggemanJ., VriendG., et al.2006. A text-mining analysis of the human phenome. Eur. J. Hum. Genet., 14, 535–542.
46.
YangX., BentinkS., ScheidS., et al.2006. Similarities of ordered gene lists. J. Bioinforma. Comput. Biol., 4(3):693–708.
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