Cited by 298Genetic Associations and EpidemiologyBioinformatics and Genomic NetworksGenetic Mapping and Diversity in Plants and Animals

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Probing genetic overlap among complex human phenotypes

Open access

Rzhetsky, Andrey, Wajngurt, David, Park, Naeun, Zheng, Tian·2007·Proceedings of the National Academy of Sciences

DOI 10.1073/pnas.0704820104PMC PMC1906727

Open this paper in CoChat — free account

Abstract

Geneticists and epidemiologists often observe that certain hereditary disorders cooccur in individual patients significantly more (or significantly less) frequently than expected, suggesting there is a genetic variation that predisposes its bearer to multiple disorders, or that protects against some disorders while predisposing to others. We suggest that, by using a large number of phenotypic observations about multiple disorders and an appropriate statistical model, we can infer genetic overlaps between phenotypes. Our proof-of-concept analysis of 1.5 million patient records and 161 disorders indicates that disease phenotypes form a highly connected network of strong pairwise correlations. Our modeling approach, under appropriate assumptions, allows us to estimate from these correlations the size of putative genetic overlaps. For example, we suggest that autism, bipolar disorder, and schizophrenia share significant genetic overlaps. Our disease network hypothesis can be immediately exploited in the design of genetic mapping approaches that involve joint linkage or association analyses of multiple seemingly disparate phenotypes.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1073/pnas.0704820104

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The Statistical Analysis of Failure Time Data
Kalbfleisch, J. D., & Prentice, R. L. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781118032985 · Cited by 3,219
The Statistical Analysis of Failure Time Data
Klein, J. P., Kalbfleisch, J. D., & Prentice, R. L. (1982) · Technometrics · doi:10.1080/00401706.1982.10487769 · Cited by 2,248
Linkage strategies for genetically complex traits. I. Multilocus models.
RISCH, N. J. (1990) · PubMed · Cited by 1,315
Population genetics of polymorphism and divergence.
Sawyer, S. A., & Hartl, D. L. (1992) · Genetics · doi:10.1093/genetics/132.4.1161 · Cited by 592
Autism and tuberous sclerosis
Smalley, S. L., Tanguay, P. E., Smith, M., & Gutierrez, G. (1992) · Journal of Autism and Developmental Disorders · doi:10.1007/bf01048239 · Cited by 511
Comprehensive Handbook of Psychopathology
Sutker, P. B., & Adams, H. E. (1993) · Springer eBooks · doi:10.1007/978-1-4615-3008-4 · Cited by 406
Human genes that limit AIDS
O’Brien, S. J., & Nelson, G. W. (2004) · Nature Genetics · doi:10.1038/ng1369 · Cited by 319
Specific Genetic Disorders and Autism: Clinical Contribution Towards their Identification
Cohen, D., Pichard, N., Tordjman, S., Baumann, C., Burglen, L., Excoffier, E., Lazar, G., Mazet, P., Pinquier, C., Verloes, A., et al. (2005) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-004-1038-2 · Cited by 316
Bipolar disorder, schizophrenia and other psychotic disorders in adults with childhood onset AD/HD and/or autism spectrum disorders
Stahlberg, O., Soderstrom, H., Rastam, M., & Gillberg, C. (2004) · Journal of Neural Transmission · doi:10.1007/s00702-004-0115-1 · Cited by 273
Medical Risk in Patients With Bipolar Disorder and Schizophrenia
Newcomer, J. W. (2006) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.1106e16 · Cited by 263

Flagged first, then by citations

Show all 15 references

Research works printed but not linked: 2

N Risch Am J Hum Genet 46, 229–241 (1990).
J Neyman, ES Pearson Biometrika 20-A, 175– 240, 263–294 (1928).

Sorted by citations

Items 101–200 of 295

Biomedical data, computational methods and tools for evaluating disease–disease associations
Xiang, J., Zhang, J., Zhao, Y., Wu, F.-X., & Li, M. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac006 · Cited by 49
Association study of the KCNJ3 gene as a susceptibility candidate for schizophrenia in the Chinese population
Yamada, K., Iwayama, Y., Toyota, T., Ohnishi, T., Ohba, H., Maekawa, M., & Yoshikawa, T. (2011) · Human Genetics · doi:10.1007/s00439-011-1089-3 · Cited by 49
Modeling autism: a systems biology approach
Randolph-Gips, M. M., & Srinivasan, P. N. (2012) · Journal of Clinical Bioinformatics · doi:10.1186/2043-9113-2-17 · Cited by 49
A phenome-guided drug repositioning through a latent variable model
Bişğin, H., Liu, Z., Fang, H., Kelly, R. J., Xu, X., & Tong, W. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-267 · Cited by 50
Mutation of Semaphorin-6A Disrupts Limbic and Cortical Connectivity and Models Neurodevelopmental Psychopathology
Rünker, A. E., O’Tuathaigh, C. M. P., Dunleavy, M., Morris, D. W., Little, G. E., Corvin, A. P., Gill, M., Henshall, D. C., Waddington, J. L., & Mitchell, K. J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026488 · Cited by 52
A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases
Zolotareva, O., & Kleine, M. (2019) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2018-0069 · Cited by 46
Rare Copy Number Deletions Predict Individual Variation in Intelligence
Yeo, R. A., Gangestad, S. W., Liu, J., Calhoun, V. D., & Hutchison, K. E. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016339 · Cited by 46
Computing disease incidence, prevalence and comorbidity from electronic medical records
Bagley, S. C., & Altman, R. B. (2016) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2016.08.005 · Cited by 46
Dislexia: enfermedad, trastorno o algo distinto
Pallarés, J. A. (2009) · Revista de Neurología · doi:10.33588/rn.48s02.2009007 · Cited by 46
Genetic mapping of habitual substance use, obesity-related traits, responses to mental and physical stress, and heart rate and blood pressure measurements reveals shared genes that are overrepresented in the neural synapse
Nikpay, M., Šeda, O., Tremblay, J., Petrovich, M., Gaudet, D., Kotchen, T. A., Cowley, A. W., & Hamet, P. (2012) · Hypertension Research · doi:10.1038/hr.2011.233 · Cited by 45
Beyond categorical diagnostics in psychiatry: Scientific and medicolegal implications
Anckarsäter, H. S. (2010) · International Journal of Law and Psychiatry · doi:10.1016/j.ijlp.2009.12.001 · Cited by 48
Research Review: Crossing syndrome boundaries in the search for brain endophenotypes
Levy, Y., & Ebstein, R. P. (2008) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2008.01986.x · Cited by 44
The human disease network
Emmert‐Streib, F., Tripathi, S., Simoes, R. D. M., Hawwa, A. F., & Dehmer, M. (2013) · Systems Biomedicine · doi:10.4161/sysb.22816 · Cited by 43
Multiplicative Effects of Social and Psychological Risk Factors on College Students’ Suicidal Behaviors
Assari, S. (2018) · Brain Sciences · doi:10.3390/brainsci8050091 · Cited by 43
Association of Genetic Variation in the MET Proto-Oncogene With Schizophrenia and General Cognitive Ability
Burdick, K. E., DeRosse, P., Kane, J. M., Lencz, T., & Malhotra, A. K. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2009.09050615 · Cited by 43
The common biological basis for common complex diseases: evidence from lipoprotein lipase gene
Xie, C., Wang, Z. C., Liu, X. F., & Yang, M. S. (2009) · European Journal of Human Genetics · doi:10.1038/ejhg.2009.134 · Cited by 42
Somatic Diseases and Conditions Before the First Diagnosis of Schizophrenia: A Nationwide Population-based Cohort Study in More Than 900 000 Individuals
Sørensen, H. J., Nielsen, P. R., Benros, M. E., Pedersen, C. B., & Mortensen, P. B. (2014) · Schizophrenia Bulletin · doi:10.1093/schbul/sbu110 · Cited by 41
Network analysis of genes and their association with diseases
Kontou, P. I., Pavlopoulou, A., Dimou, N. L., Pavlopoulos, G. A., & Bagos, P. G. (2016) · Gene · doi:10.1016/j.gene.2016.05.044 · Cited by 43
RETRACTED: A computational approach to identify blood cell-expressed Parkinson's disease biomarkers that are coordinately expressed in brain tissue
Moni, M. A., Rana, H. K., Islam, M. B., Ahmed, M. B., Xu, H., Hasan, M. A. M., Lei, Y., & Quinn, J. M. W. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.103385 · Cited by 41
Retracted
Network Physiology of Exercise: Beyond Molecular and Omics Perspectives
Balagué, N., Hristovski, R., Almarcha, M., García‐Retortillo, S., & Ivanov, P. C. (2022) · Sports Medicine - Open · doi:10.1186/s40798-022-00512-0 · Cited by 40
Genetic insights into cardiometabolic risk factors.
Whitfield, J. B. (2014) · Europe PMC (PubMed Central) · Cited by 40
Association study of PDE4B gene variants in scandinavian schizophrenia and bipolar disorder multicenter case–control samples
Kähler, A. K., Otnæss, M. K., Wirgenes, K. V., Hansen, T. F., Jönsson, E. G., Agartz, I., Hall, H., Werge, T. M., Morken, G., Mors, O. N., et al. (2009) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30958 · Cited by 39
Sexually dimorphic features of vermis morphology in bipolar disorder
Womer, F. Y., Wang, F., Chepenik, L. G., Kalmar, J. H., Spencer, L., Edmiston, E. K., Pittman, B. P., Constable, R. T., Papademetris, X., & Blumberg, H. P. (2009) · Bipolar Disorders · doi:10.1111/j.1399-5618.2009.00745.x · Cited by 38
Pivotal role of the muscle-contraction pathway in cryptorchidism and evidence for genomic connections with cardiomyopathy pathways in RASopathies
Cannistraci, C. V., Ogorevc, J., Zorc, M., Ravasi, T., Dovč, P., & Kunej, T. (2013) · BMC Medical Genomics · doi:10.1186/1755-8794-6-5 · Cited by 36
Disentangling genetic and environmental risk factors for individual diseases from multiplex comorbidity networks
Klimek, P., Aichberger, S., & Stefan Thurner, A. (2016) · Scientific Reports · doi:10.1038/srep39658 · Cited by 39
Disease classification: from phenotypic similarity to integrative genomics and beyond
Dozmorov, M. G. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby049 · Cited by 36
Evaluating disease similarity based on gene network reconstruction and representation
Li, Y., Keqi, W., & Wang, G. (2021) · Computer applications in the biosciences · doi:10.1093/bioinformatics/btab252 · Cited by 36
Human Pathway-Based Disease Network
Yu, L., & Gao, L. (2017) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2017.2774802 · Cited by 35
Genome‐wide significant localization for working and spatial memory: Identifying genes for psychosis using models of cognition
Knowles, E. E. M., Carless, M. A., Almeida, M., Curran, J. E., McKay, D., Sprooten, E., Dyer, T. D., Göring, H. H. H., Olvera, R. L., Fox, P. T., et al. (2013) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32211 · Cited by 35
A Schizophrenia Gene Locus on Chromosome 17q21 in a New Set of Families of Mexican and Central American Ancestry: Evidence From the NIMH Genetics of Schizophrenia in Latino Populations Study
Escamilla, M., Hare, E., Dassori, A. M., Peralta, J. M., Ontiveros, A., Nicolini, H., Raventós, H., Medina, R., Mendoza, R., Jerez, A., et al. (2009) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2008.08040612 · Cited by 35
Large-scale mining disease comorbidity relationships from post-market drug adverse events surveillance data
Zheng, C., & Xu, R. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2468-8 · Cited by 35
Phenotype-genotype comorbidity analysis of patients with rare disorders provides insight into their pathological and molecular bases
Díaz-Santiago, E., Jabato, F. M., Rojano, E., Seoane, P., Pazos, F., Perkins, J. R., & Ranea, J. A. G. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009054 · Cited by 34
Network medicine: linking disorders
Piro, R. M. (2012) · Human Genetics · doi:10.1007/s00439-012-1206-y · Cited by 34
Network-based identification of genetic factors in ageing, lifestyle and type 2 diabetes that influence to the progression of Alzheimer's disease
Chowdhury, U. N., Ahmad, S., Islam, M. B., Huq, F., Quinn, J. M. W., & Moni, M. A. (2020) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2020.100309 · Cited by 34
Clinical phenotype network: the underlying mechanism for personalized diagnosis and treatment of traditional Chinese medicine
Zhou, X., Li, Y., Peng, Y., Hu, J., Zhang, R., He, L., Wang, Y., Jiang, L., Yan, S., Li, P., et al. (2014) · Frontiers of Medicine · doi:10.1007/s11684-014-0349-8 · Cited by 33
Calibration of credibility of agnostic genome‐wide associations
Ioannidis, J. P. A. (2008) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30721 · Cited by 33
Constraints on Biological Mechanism from Disease Comorbidity Using Electronic Medical Records and Database of Genetic Variants
Bagley, S. C., Sirota, M., Chen, R., Butte, A. J., & Altman, R. B. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004885 · Cited by 32
Genetic bases of human comorbidity
Puzyrev, V. P. (2015) · Russian Journal of Genetics · doi:10.1134/s1022795415040092 · Cited by 32
Adults with autism spectrum conditions experience increased levels of anomalous perception
Milne, E., Dickinson, A. H., & Smith, R. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177804 · Cited by 31
Machine learning and network-based models to identify genetic risk factors to the progression and survival of colorectal cancer
Hossain, M. J., Chowdhury, U. N., Islam, M. B., Uddin, S., Ahmed, M. B., Quinn, J. M. W., & Moni, M. A. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104539 · Cited by 31
Automated ontological gene annotation for computing disease similarity.
Mathur, S., & Dinakarpandian, D. (2010) · PubMed Central · Cited by 31
Introduction to correlation networks: Interdisciplinary approaches beyond thresholding
Masuda, N., Boyd, Z. M., Garlaschelli, D., & Mucha, P. J. (2025) · Physics Reports · doi:10.1016/j.physrep.2025.06.002 · Cited by 40
Insights into pathophysiology of dystropy through the analysis of gene networks: an example of bronchial asthma and tuberculosis
Bragina, E. Y., Tiys, E., Freidin, M. B., Koneva, L. A., Сергеевич, Д. П., Иванисенко, В. А., Kolchanov, N. A., & Puzyrev, V. P. (2014) · Immunogenetics · doi:10.1007/s00251-014-0786-1 · Cited by 30
The human disease network in terms of dysfunctional regulatory mechanisms
Yang, J., Wu, S.-J., Dai, W., Li, Y., & Li, Y. (2015) · Biology Direct · doi:10.1186/s13062-015-0088-z · Cited by 29
The genetics of cognitive impairment in schizophrenia: a phenomic perspective
Bilder, R. M., Howe, A., Novak, N. M., Sabb, F. W., & Parker, D. S. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.07.002 · Cited by 29
Predictive Value of Morphological Features in Patients with Autism versus Normal Controls
Özgen, M. H., Hellemann, G., de Jonge, M. V., Beemer, F. A., & van Engeland, H. (2012) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-012-1554-4 · Cited by 30
A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations
Guo, X., Gao, L., Wei, C., Yang, X., Zhao, Y. C., & Dong, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024171 · Cited by 28
Suggestive Linkage of the Child Behavior Checklist Juvenile Bipolar Disorder Phenotype to 1p21, 6p21, and 8q21
Doyle, A. E., Biederman, J., Ferreira, M. A. R., Wong, P. M., Smoller, J. W., & Faraone, S. V. (2010) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2010.01.008 · Cited by 27
Discerning asthma endotypes through comorbidity mapping
Jia, G., Zhong, X. Y., Im, H. K., Schoettler, N., Pividori, M., Hogarth, D. K., Sperling, A. I., White, S. R., Naureckas, E. T., Lyttle, C. S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33628-8 · Cited by 29
Self-citation
Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network
Al‐Harazi, O., Insaif, S. A., Al-Ajlan, M., Kaya, N., Dzimiri, N., & Çolak, D. (2015) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2015.11.002 · Cited by 28
Risk of Alzheimer’s Disease in Cancer Patients: Analysis of Mortality Data from the US SEER Population-Based Registries
Mezencev, R., & Chernoff, Y. O. (2020) · Cancers · doi:10.3390/cancers12040796 · Cited by 27
Association of MCTP2 gene variants with schizophrenia in three independent samples of Scandinavian origin (SCOPE)
Djurovic, S., Hellard, S. L., Kähler, A. K., Jönsson, E. G., Agartz, I., Steen, V. M., Hall, H., Wang, A. G., Rasmussen, H. B., Melle, I. S., et al. (2009) · Psychiatry Research · doi:10.1016/j.psychres.2008.08.007 · Cited by 24
Alzheimers Disease and Intelligence
Yeo, R. A., Arden, R., & Jung, R. E. (2011) · Current Alzheimer Research · doi:10.2174/156720511795745276 · Cited by 25
Big Data Reveal Insights into Alopecia Areata Comorbidities
Lim, C.-P., Severin, R. K., & Petukhova, L. (2017) · Journal of Investigative Dermatology Symposium Proceedings · doi:10.1016/j.jisp.2017.10.006 · Cited by 24
Molecular network analysis enhances understanding of the biology of mental disorders
Grennan, K. S., Chen, C., Gershon, E. S., & Liu, C. (2014) · BioEssays · doi:10.1002/bies.201300147 · Cited by 24
Disease Comorbidity Network Guides the Detection of Molecular Evidence for the Link Between Colorectal Cancer and Obesity.
Chen, Y., Li, L., & Xu, R. (2015) · Europe PMC (PubMed Central) · Cited by 23
An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data
Mugzach, O., Mor Peleg, B., Bagley, S. C., Guter, S. J., Cook, E. H., & Altman, R. B. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.06.026 · Cited by 23
Disease classification via gene network integrating modules and pathways
Mi, Z., Guo, B., Yin, Z., Li, J., & Zheng, Z. (2019) · Royal Society Open Science · doi:10.1098/rsos.190214 · Cited by 23
Autworks: a cross-disease network biology application for Autism and related disorders
Nelson, T. H., Jung, J.-Y., DeLuca, T. F., Hinebaugh, B. K., Gabriel, K. C. S., & Wall, D. P. (2012) · BMC Medical Genomics · doi:10.1186/1755-8794-5-56 · Cited by 22
An electronic medical record-linked biorepository to identify novel biomarkers for atherosclerotic cardiovascular disease
Ye, Z., Kalloo, F. S., Dalenberg, A. K., & Kullo, I. J. (2013) · Global Cardiology Science and Practice · doi:10.5339/gcsp.2013.10 · Cited by 23
Evaluating Wikipedia as a Source of Information for Disease Understanding
del Valle, E. P. G., Garcia, G. L., Santamaria, L. P., Zanin, M., Ruiz, E. M., & Gonzalez, A. R. (2018) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2018.00076 · Cited by 21
Коморбідність: сучасний погляд на проблему; класифікація (повідомлення перше)
Abrahamovych, O., Fayura, O., & Abrahamovych, U. (2015) · Lviv clinical bulletin · doi:10.25040/lkv2015.04.056 · Cited by 21
Combinations of newly confirmed Glioma-Associated loci link regions on chromosomes 1 and 9 to increased disease risk
Yang, T.-H., Kon, M., Hung, J., & DeLisi, C. (2011) · BMC Medical Genomics · doi:10.1186/1755-8794-4-63 · Cited by 21
Unique genetic and risk-factor profiles in clusters of major depressive disorder-related multimorbidity trajectories
Gézsi, A., der Auwera, S. V., Mäkinen, H., Eszlári, N., Hullám, G., Nagy, T., Bonk, S., González, R., Gonda, X., Garvert, L., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51467-7 · Cited by 23
A Drug-Centric View of Drug Development: How Drugs Spread from Disease to Disease
Rodriguez‐Esteban, R. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004852 · Cited by 20
Suicide Attempts in Michigan HealthCare System; Racial Differences
Assari, S. (2018) · Brain Sciences · doi:10.3390/brainsci8070124 · Cited by 20
Molecular Relationships between Bronchial Asthma and Hypertension as Comorbid Diseases
Bragina, E. Y., Goncharova, I. A., Garaeva, A. F., Владимирович, Н. Е., Babovskaya, A. A., Карпов, А. Б., Semenova, Y. V., Zhalsanova, I. Z., Gomboeva, D. E., Saik, O., et al. (2018) · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics · doi:10.1515/jib-2018-0052 · Cited by 20
Human Genetics: The Hidden Text of Genome-wide Associations
Gibson, G. C., & Goldstein, D. B. (2007) · Current Biology · doi:10.1016/j.cub.2007.08.044 · Cited by 19
Genetic View on the Phenomenon of Combined Diseases in Man
Puzyrev, V. P., & Freidin, M. B. (2009) · Acta Naturae · doi:10.32607/20758251-2009-1-3-52-57 · Cited by 19
Network Analysis of Human Disease Comorbidity Patterns Based on Large-Scale Data Mining
Chen, Y., & Xu, R. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-08171-7_22 · Cited by 18
Identification of novel susceptibility genes associated with seven autoimmune disorders using whole genome molecular interaction networks
Kara, S., Pirela-Morillo, G. A., Gilliam, T. C., & Wilson, G. D. (2018) · Journal of Autoimmunity · doi:10.1016/j.jaut.2018.10.002 · Cited by 18
Discussion of “Biomedical Ontologies: Toward Scientific Debate”
Brochhausen, M., Burgun, A., Ceusters, W. M., Hasman, A., Leong, T.-Y., Musen, M. A., Oliveira, J. L., Mor Peleg, B., Rector, A. L., & Schulz, S. (2011) · Methods of Information in Medicine · doi:10.1055/s-0038-1625243 · Cited by 18
Sensitivity of comorbidity network analysis
Brunson, J. C., Agresta, T. P., & Laubenbacher, R. (2019) · JAMIA Open · doi:10.1093/jamiaopen/ooz067 · Cited by 17
Taking Bioinformatics to Systems Medicine
van Kampen, A. H. C., & Moerland, P. D. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-3283-2_2 · Cited by 17
Mining Cancer-Specific Disease Comorbidities from a Large Observational Health Database
Chen, Y., & Xu, R. (2014) · Cancer Informatics · doi:10.4137/cin.s13893 · Cited by 17
Syndrome métabolique chez les patients atteints de schizophrénie indépendamment de la prise d’antipsychotiques atypiques
Khalil, R. B. (2011) · La Presse Médicale · doi:10.1016/j.lpm.2011.10.013 · Cited by 19
Finding Genetic Overlaps Among Diseases Based on Ranked Gene Lists
Chen, Q., Zhou, X. J., & Sun, F. (2015) · Journal of Computational Biology · doi:10.1089/cmb.2014.0149 · Cited by 16
A system-level analysis of patient disease trajectories based on clinical, phenotypic and molecular similarities
Giannoula, A., Centeno, E., Mayer, M. Á., Sanz, F., & Furlong, L. I. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa964 · Cited by 16
Syntropy, Genetic Testing and Personalized Medicine
Puzyrev, V. P., Makeeva, O. A., & Freidin, M. B. (2010) · Personalized Medicine · doi:10.2217/pme.10.35 · Cited by 16
Autism Spectrum Disorders: The Role of Genetics in Diagnosis and Treatment
Deutsch, S. I. (2011) · InTech eBooks · doi:10.5772/976 · Cited by 16
Data-driven comorbidity analysis of 100 common disorders reveals patient subgroups with differing mortality risks and laboratory correlates
Koskinen, M., Salmi, J. K., Loukola, A., Mäkelä, M. J., Sinisalo, J. P., Carpén, O., & Renkonen, R. (2022) · Scientific Reports · doi:10.1038/s41598-022-23090-3 · Cited by 15
Association of the Catechol-o-Methyltransferase Gene Polymorphisms with Korean Autism Spectrum Disorders
Yoo, H. J., Cho, I. H., Park, M., Yang, S. Y., & Kim, S. A. (2013) · Journal of Korean Medical Science · doi:10.3346/jkms.2013.28.9.1403 · Cited by 15
Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome
Akram, P., & Liao, L. (2017) · BMC Genomics · doi:10.1186/s12864-017-4272-7 · Cited by 15
Diagnosis and Revision of the Classification Systems
Jablensky, A. V. (2011) · Wiley eBooks · doi:10.1002/9780470978672.ch1 · Cited by 15
Genetics of Autism
Abrahams, B. S., & Geschwind, D. H. (2009) · Springer eBooks · doi:10.1007/978-3-540-37654-5_29 · Cited by 15
Where do obesity and male infertility collide?
Jahangir, M., Nazari, M., Babakhanzadeh, E., & Manshadi, S. D. (2024) · BMC Medical Genomics · doi:10.1186/s12920-024-01897-5 · Cited by 13
Case-Control Study in China of Risk Factors for Suicide in Men With Alcohol Use Disorders
Zhang, Y., Conner, K. R., & Phillips, M. R. (2012) · Journal of Studies on Alcohol and Drugs · doi:10.15288/jsad.2012.73.15 · Cited by 13
Molecular mechanistic associations of human diseases
Stegmaier, P., Krull, M., Voss, N., Kel, A. E., & Wingender, E. (2010) · BMC Systems Biology · doi:10.1186/1752-0509-4-124 · Cited by 13
Introduction to Epigenetics in Psychiatry
Lee, R. S., & Avramopoulos, D. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-417114-5.00001-2 · Cited by 14
MET and AKT Genetic Influence on Facial Emotion Perception
Lin, M.-T., Huang, K.-H., Huang, C.-L., Huang, Y.-J., Tsai, G. E., & Lane, H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036143 · Cited by 13
Minimising Information Loss on Anonymised High Dimensional Data with Greedy In-Memory Processing
Podlesny, N. J., Kayem, A. V. D. M., von Schorlemer, S., & Uflacker, M. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-98809-2_6 · Cited by 13
Measuring the importance of vertices in the weighted human disease network
Almasi, S. M., & Hu, T. (2019) · PLoS ONE · doi:10.1371/journal.pone.0205936 · Cited by 13
Integrative network analysis interweaves the missing links in cardiomyopathy diseasome
Chauhan, P. K., & Sowdhamini, R. (2022) · Scientific Reports · doi:10.1038/s41598-022-24246-x · Cited by 12
Finding directionality and gene-disease predictions in disease associations
Albornoz, M. G., & Nielsen, J. (2015) · BMC Systems Biology · doi:10.1186/s12918-015-0184-9 · Cited by 12
Attribute Compartmentation and Greedy UCC Discovery for High-Dimensional Data Anonymization
Podlesny, N. J., Kayem, A. V. D. M., & Meinel, C. (2019) · ACM Conference on Data and Application Security and Privacy (CODASPY) · doi:10.1145/3292006.3300019 · Cited by 12
The Alzheimer’s comorbidity phenome: mining from a large patient database and phenome-driven genetics prediction
Zheng, C., & Xu, R. (2018) · JAMIA Open · doi:10.1093/jamiaopen/ooy050 · Cited by 12
GenCoNet – A Graph Database for the Analysis of Comorbidities by Gene Networks
Shoshi, A., Hofestädt, R., Zolotareva, O. I., Friedrichs, M., Maier, A., Иванисенко, В. А., Dosenko, V., & Bragina, E. Y. (2018) · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics · doi:10.1515/jib-2018-0049 · Cited by 12
The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci
Jia, G., Li, Y., Zhong, X. Y., Wang, K., Pividori, M., Alomairy, R., Esposito, A., Ltaief, H., Terao, C. C., Akiyama, M., et al. (2023) · Nature Computational Science · doi:10.1038/s43588-023-00453-y · Cited by 11
Self-citation
RASopathies: Presentation at the Genome, Interactome, and Phenome Levels
Pevec, U., Rozman, N., Gorsek, B., & Kunej, T. (2016) · Molecular Syndromology · doi:10.1159/000445733 · Cited by 11
Human disease cost network analysis
Ma, C., Li, Y., Shia, B., & Ma, S. (2020) · Statistics in Medicine · doi:10.1002/sim.8472 · Cited by 11

Authors: Rzhetsky, A., Wajngurt, D., Park, N., & Zheng, T.
Affiliations: Columbia University (US)
*Department of Biomedical Informatics, Center for Computational Biology and Bioinformatics and Joint Centers for Systems Biology, and
ORCID: Rzhetsky, Andrey
Zheng, Tian
Venue: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences
Published: 2007-07-10
Volume: 104
Issue: 28
Pages: 11694-11699
ISSN: 0027-8424 (ISSN-L)
1091-6490
DOI: 10.1073/pnas.0704820104
PMC: PMC1906727
OpenAlex: W2121926780
Cited by: 298
References: 15
Citations by year: 2026: 4 · 2025: 2 · 2024: 9 · 2023: 4 · 2022: 10 · 2021: 8 · 2020: 9 · 2019: 20 · 2018: 16 · 2017: 15 · 2016: 12 · 2015: 28 · 2014: 24 · 2013: 22 · 2012: 17
FWCI: 12.55
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Proceedings of the National Academy of Sciences (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Columbia Academic Commons (Columbia University)
Funders: National Science Foundation (0121687, 0438291, 0532231)
National Institutes of Health (CA121852, U54-CA121852)
Advanced Research Projects Agency
National Cancer Institute (U54CA121852)
National Institute of General Medical Sciences (GM61372, R01GM061372, GM070789, R01GM070789)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords: genetic overlap, disease networks, genetic correlation, comorbidities, autism spectrum disorder, bipolar disorder, schizophrenia, gene mapping
MeSH terms: Autistic Disorder, Bipolar Disorder, Humans, Models, Genetic, Phenotype, Schizophrenia, Genetic Variation, Genome, Human, Likelihood Functions

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Probing genetic overlap among complex human phenotypes

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks