Personal genomes: The case of the missing heritability

Transposable elements: targets for early nutritional effects on epigenetic gene regulation

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Large recurrent microdeletions associated with schizophrenia.

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Rare chromosomal deletions and duplications increase risk of schizophrenia

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Genetic Dissection of Transcriptional Regulation in Budding Yeast

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Genome-wide association analysis identifies 20 loci that influence adult height

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Many sequence variants affecting diversity of adult human height

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The genetics of autistic disorders and its clinical relevance: a review of the literature

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Identification of ten loci associated with height highlights new biological pathways in human growth

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Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL

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Sizing up human height variation

Visscher, P. M. (2008) · Nature Genetics · doi:10.1038/ng0508-489 · Cited by 474

Joint influence of small-effect genetic variants on human longevity

Yashin, A. I., Wu, D., Arbeev, K. G., & Ukraintseva, S. V. (2010) · Aging · doi:10.18632/aging.100191 · Cited by 81

Next-generation metabolomics in lung cancer diagnosis, treatment and precision medicine: mini review

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Predicting genetic modifier loci using functional gene networksPreprint

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Genetic Research into Bipolar Disorder: The Need for a Research Framework that Integrates Sophisticated Molecular Biology and Clinically Informed Phenotype Characterization

Schulze, T. G. (2010) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2009.10.005 · Cited by 80

The complete and fully-phased diploid genome of a male Han Chinese

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Inequality at Birth: Some Causes and Consequences

Currie, J. (2011) · National Bureau of Economic Research · doi:10.3386/w16798 · Cited by 79

Genetics of Callous-Unemotional Behavior in Children

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Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

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Application of Whole-Genome Prediction Methods for Genome-Wide Association Studies: A Bayesian Approach

Fernando, R. L., Toosi, A., Wolc, A., Garrick, D. J., & Dekkers, J. C. M. (2017) · Journal of Agricultural Biological and Environmental Statistics · doi:10.1007/s13253-017-0277-6 · Cited by 79

Analysis of Gene‐Gene Interactions

Cole, B. S., Hall, M. A., Urbanowicz, R. J., Gilbert‐Diamond, D., & Moore, J. H. (2017) · Current Protocols in Human Genetics · doi:10.1002/cphg.45 · Cited by 78

Genetic Variation Throughout the Folate Metabolic Pathway Influences Negative Symptom Severity in Schizophrenia

Roffman, J. L., Brohawn, D. G., Nitenson, A. Z., Macklin, E. A., Smoller, J. W., & GOFF, D. C. (2011) · Schizophrenia Bulletin · doi:10.1093/schbul/sbr150 · Cited by 81

The emerging molecular architecture of schizophrenia, polygenic risk scores and the clinical implications for GxE research

Iyegbe, C. O., Campbell, D., Butler, A. W., Ajnakina, O., & Sham, P. C. (2014) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-014-0823-2 · Cited by 78

Improving genetic risk prediction by leveraging pleiotropy

Li, C., Yang, C., Gelernter, J. E., & Zhao, H. (2013) · Human Genetics · doi:10.1007/s00439-013-1401-5 · Cited by 77

New findings in the genetics of major psychoses

Nöthen, M. M., Nieratschker, V., Cichon, S., & Rietschel, M. (2010) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2010.12.1/mnoethen · Cited by 76

GWAS: heritability missing in action?

Clarke, A. J., & Cooper, D. N. (2010) · European Journal of Human Genetics · doi:10.1038/ejhg.2010.35 · Cited by 79

Anthropology Meets Epigenetics: Current and Future Directions

Thayer, Z. M., & Non, A. L. (2015) · American Anthropologist · doi:10.1111/aman.12351 · Cited by 74

Relational mate value: Consensus and uniqueness in romantic evaluations.

Eastwick, P. W., & Hunt, L. L. (2014) · Journal of Personality and Social Psychology · doi:10.1037/a0035884 · Cited by 75

Whole-genome association study for fatty acid composition of oleic acid in Japanese Black cattle

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First Genome-Wide Association Study on Anxiety-Related Behaviours in Childhood

Trzaskowski, M., Eley, T. C., Davis, O. S. P., Doherty, S. J., Hanscombe, K. B., Meaburn, E. L., Haworth, C. M. A., Price, T. S., & Plomin, R. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0058676 · Cited by 75

A method for generating realistic correlation matrices

Hardin, J., Garcia, S. R., & Golan, D. (2013) · The Annals of Applied Statistics · doi:10.1214/13-aoas638 · Cited by 79

Single Nucleotide Polymorphisms in the Insulin-Like Growth Factor 1 (IGF-1) Gene are Associated with Performance in Holstein-Friesian Dairy Cattle

Mullen, M. P., Berry, D. P., Howard, D. J., Diskin, M. G., Lynch, C. O., Giblin, L., Kenny, D. A., Magee, D. A., Meade, K. G., & Waters, S. M. (2011) · Frontiers in Genetics · doi:10.3389/fgene.2011.00003 · Cited by 77

Using Biological Knowledge to Uncover the Mystery in the Search for Epistasis in Genome-Wide Association Studies

Ritchie, M. D. (2010) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2010.00630.x · Cited by 76

Population Growth Inflates the Per-Individual Number of Deleterious Mutations and Reduces Their Mean Effect

Gazave, É., Chang, D., Clark, A. G., & Keinan, A. (2013) · Genetics · doi:10.1534/genetics.113.153973 · Cited by 76

The success of pharmacogenomics in moving genetic association studies from bench to bedside: study design and implementation of precision medicine in the post-GWAS era

Ritchie, M. D. (2012) · Human Genetics · doi:10.1007/s00439-012-1221-z · Cited by 78

Complex-Trait Prediction in the Era of Big Data

Campos, G. D. L., Vazquez, A. I., Hsu, S., & Lello, L. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.07.004 · Cited by 71

Ancestral paternal genotype controls body weight and food intake for multiple generations

Yazbek, S. N., Spiezio, S. H., Nadeau, J. H., & Buchner, D. A. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq332 · Cited by 73

Evidence from pyrosequencing indicates that natural variation in animal personality is associated with DRD 4 DNA methylation

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Relationship between genomic distance-based regression and kernel machine regression for multi-marker association testing

Pan, W. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20567 · Cited by 71

Genetics of Eating Disorders

Hinney, A., & Volckmar, A. (2013) · Current Psychiatry Reports · doi:10.1007/s11920-013-0423-y · Cited by 77

The genetics of childhood obesity and interaction with dietary macronutrients

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Genomic sequencing in clinical practice: applications, challenges, and opportunities

Krier, J. B., Kalia, S. S., & Green, R. C. (2016) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2016.18.3/jkrier · Cited by 72

Machine Learning and Radiogenomics: Lessons Learned and Future Directions

Kang, J., Rancati, T., Lee, S., Oh, J. H., Kerns, S. L., Scott, J. G., Schwartz, R. S., Kim, S. Y., & Rosenstein, B. S. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00228 · Cited by 74

Complement activation as a biomarker for Alzheimer's disease

Aiyaz, M., Lupton, M. K., Proitsi, P., Powell, J. F., & Lovestone, S. (2011) · Immunobiology · doi:10.1016/j.imbio.2011.07.023 · Cited by 69

Performance analysis of novel methods for detecting epistasis

Shang, J., Zhang, J., Sun, Y., Liu, D., Ye, D., & Yin, Y. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-475 · Cited by 70

Missing heritability of complex diseases: Enlightenment by genetic variants from intermediate phenotypes

Blanco‐Gómez, A., Castillo‐Lluva, S., Sáez‐Freire, M. D. M., Hontecillas‐Prieto, L., Mao, J., Castellanos‐Martín, A., & Pérez‐Losada, J. (2016) · BioEssays · doi:10.1002/bies.201600084 · Cited by 72

On the Accuracy of Genomic Selection

Rabier, C., Barré, P., Asp, T., Charmet, G., & Mangin, B. (2016) · PLoS ONE · doi:10.1371/journal.pone.0156086 · Cited by 73

Knowledge-Driven Analysis Identifies a Gene–Gene Interaction Affecting High-Density Lipoprotein Cholesterol Levels in Multi-Ethnic Populations

Ma, L., Brautbar, A., Boerwinkle, E., Sing, C. F., Clark, A. G., & Keinan, A. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002714 · Cited by 70

Pathway-based discovery of genetic interactions in breast cancer

Wang, W., Xu, Z., Costanzo, M., Boone, C. M., Lange, C. A., & Myers, C. L. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006973 · Cited by 68

Polygenic Scores in Epidemiology: Risk Prediction, Etiology, and Clinical Utility

Maher, B. S. (2015) · Current Epidemiology Reports · doi:10.1007/s40471-015-0055-3 · Cited by 69

Performance of Genotype Imputation for Low Frequency and Rare Variants from the 1000 Genomes

Zheng, H., Rong, J., Liu, M., Han, F., Zhang, X., Richards, J. B., & Wang, L. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116487 · Cited by 72

The influence of race and ethnicity on the biology of cancer

Henderson, B. E., Lee, N. H., Seewaldt, V. L., & Shen, H. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3341 · Cited by 68

Epigenesis for epidemiologists: does evo-devo have implications for population health research and practice?

Davey Smith, G. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys016 · Cited by 68

Predicting Thermal Adaptation by Looking Into Populations’ Genomic Past

Cortés, A. J., López-Hernández, F., & Osorio-Rodríguez, D. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.564515 · Cited by 66

Genome–Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Cortés, A. J., López-Hernández, F., & Blair, M. W. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.910386 · Cited by 70

Genome-wide identification of inter-individually variable DNA methylation sites improves the efficacy of epigenetic association studies

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Association of smoking and polygenic risk with the incidence of lung cancer: a prospective cohort study

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Genetic regulation of adult stature

Lettre, G. (2009) · Current Opinion in Pediatrics · doi:10.1097/mop.0b013e32832c6dce · Cited by 70

Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach

Urbanowicz, R. J., Andrew, A. S., Karagas, M. R., & Moore, J. H. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001574 · Cited by 67

Quantitative Epigenetics Through Epigenomic Perturbation of Isogenic Lines

Johannes, F. M., & Colomé‐Tatché, M. (2011) · Genetics · doi:10.1534/genetics.111.127118 · Cited by 66

Targeted Resequencing and Systematic In Vivo Functional Testing Identifies Rare Variants in MEIS1 as Significant Contributors to Restless Legs Syndrome

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Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle

Jensen, J., Su, G., & Madsen, P. (2012) · BMC Genetics · doi:10.1186/1471-2156-13-44 · Cited by 65

Genome-wide association study of lung function phenotypes in a founder population

Yao, T., Du, G., Han, L., Sun, Y., Hu, D., Yang, J. J., Mathias, R. A., Roth, L. A., Rafaels, N. M., Thompson, E. E., et al. (2013) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2013.06.018 · Cited by 65

Genetics of rheumatoid arthritis: time for a change!

de Vries, R. (2011) · Current Opinion in Rheumatology · doi:10.1097/bor.0b013e3283457524 · Cited by 64

Genome-wide association study for colorectal cancer identifies risk polymorphisms in German familial cases and implicates MAPK signalling pathways in disease susceptibility

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Current understanding of human genetics and genetic analysis of psoriasis

Oka, A., Mabuchi, T., OZAWA, A., & Inoko, H. (2012) · The Journal of Dermatology · doi:10.1111/j.1346-8138.2012.01504.x · Cited by 63

Genetic risk sum score comprised of common polygenic variation is associated with body mass index

Peterson, R. E., MAES, H. H. M., Holmans, P., Sanders, A. R., Levinson, D. F., Shi, J., Kendler, K. S., Gejman, P. V., & Webb, B. T. (2010) · Human Genetics · doi:10.1007/s00439-010-0917-1 · Cited by 64

On high-dimensional misspecified mixed model analysis in genome-wide association study

Jiang, J., Li, C., Paul, D., Yang, C., & Zhao, H. (2016) · The Annals of Statistics · doi:10.1214/15-aos1421 · Cited by 63

A Meta-analysis of Heritability of Cognitive Aging: Minding the “Missing Heritability” Gap

Reynolds, C. A., & Finkel, D. (2015) · Neuropsychology Review · doi:10.1007/s11065-015-9280-2 · Cited by 63

Genes in Context

Champagne, F. A., & Rahia Mashoodh, A. (2009) · Current Directions in Psychological Science · doi:10.1111/j.1467-8721.2009.01622.x · Cited by 62

Genome-wide pleiotropy of osteoporosis-related phenotypes: The framingham study

Karasik, D., Hsu, Y., Zhou, Y., Cupples, L. A., Kiel, D. P., & Demissie, S. (2010) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.38 · Cited by 63

DNA methylation mediates genotype and smoking interaction in the development of anti-citrullinated peptide antibody-positive rheumatoid arthritis

Meng, W., Zhu, Z., Jiang, X., Too, C. L., Uebe, S., Jagodic, M., Kockum, I. S., Murad, S., Ferrucci, L., Alfredsson, L. S., et al. (2017) · Arthritis Research & Therapy · doi:10.1186/s13075-017-1276-2 · Cited by 64

Synthetic associations in the context of genome-wide association scan signals

Orozco, G., Barrett, J. C., & Zeggini, E. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq368 · Cited by 61

Early life trauma, depression and the glucocorticoid receptor gene—An epigenetic perspective

Smart, C., Strathdee, G., Watson, S., Murgatroyd, C., & McAllister-Williams, R. H. (2015) · Psychological Medicine · doi:10.1017/s0033291715001555 · Cited by 61

Why the missing heritability might not be in the DNA

Bourrat, P., Lu, Q., & Jablonka, E. (2017) · BioEssays · doi:10.1002/bies.201700067 · Cited by 61

Transmission ratio distortion: review of concept and implications for genetic association studies

Huang, L. O., Labbe, A., & Infante‐Rivard, C. (2012) · Human Genetics · doi:10.1007/s00439-012-1257-0 · Cited by 62

Coriell Personalized Medicine Collaborative ® : A Prospective Study of the Utility Of Personalized Medicine

Keller, M., Gordon, E. S., Stack, C. B., Gharani, N., Sill, C. J., Schmidlen, T., Mintzer, J. L., Pallies, J., Gerry, N. P., & Christman, M. F. (2010) · Personalized Medicine · doi:10.2217/pme.10.13 · Cited by 61

A new method for exploring gene–gene and gene–environment interactions in GWAS with tree ensemble methods and SHAP values

Johnsen, P. V., Riemer–Sørensen, S., DeWan, A. T., Cahill, M. E., & Langaas, M. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04041-7 · Cited by 64

The Cannabinoid Receptor type 2 Q63R variant increases the risk of celiac disease: Implication for a novel molecular biomarker and future therapeutic intervention

Rossi, F., Bellini, G., Tolone, C., Luongo, L., Mancusi, S., Papparella, A., Sturgeon, C., Fasano, A., Nobili, B., Perrone, L., et al. (2012) · Pharmacological Research · doi:10.1016/j.phrs.2012.03.011 · Cited by 60

Transgenerational Genetic Effects of the Paternal Y Chromosome on Daughters‘ Phenotypes

Nelson, V. R., Spiezio, S. H., & Nadeau, J. H. (2010) · Epigenomics · doi:10.2217/epi.10.26 · Cited by 60

Haplotype Analysis Improved Evidence for Candidate Genes for Intramuscular Fat Percentage from a Genome Wide Association Study of Cattle

Barendse, W. (2011) · PLoS ONE · doi:10.1371/journal.pone.0029601 · Cited by 61

Genetic variants and their interactions in disease risk prediction – machine learning and network perspectives

Okser, S., Pahikkala, T., & Aittokallio, T. A. (2013) · BioData Mining · doi:10.1186/1756-0381-6-5 · Cited by 64

Meta-analysis of 20 genome-wide linkage studies evidenced new regions linked to asthma and atopy

Bouzigon, E., Forabosco, P., Koppelman, G. H., Cookson, W., Dizier, M., Duffy, D. L., Evans, D. M., Ferreira, M. A. R., Kere, J., Laitinen, T., et al. (2010) · European Journal of Human Genetics · doi:10.1038/ejhg.2009.224 · Cited by 61

Genotype Imputation of M etabochip SNPs Using a Study‐Specific Reference Panel of ∼4,000 Haplotypes in A frican A mericans From the Women's Health Initiative

Liu, E. Y., Buyske, S. G., Aragaki, A. K., Peters, U., Boerwinkle, E., Carlson, C., Carty, C. L., Crawford, D. C., Haessler, J., Hindorff, L. A., et al. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21603 · Cited by 60

Genome-wide association studies of drought-related metabolic changes in maize using an enlarged SNP panel

Zhang, X., Warburton, M. L., Setter, T. L., Liu, H., Xue, Y., Yang, N., Yan, J., & Xiao, Y. (2016) · Theoretical and Applied Genetics · doi:10.1007/s00122-016-2716-0 · Cited by 63

Bridging the Gap Between Modern Evolutionary Psychology and the Study of Individual Differences

Penke, L. (2010) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195372090.003.0009 · Cited by 61

The Nature of Genetic Variation for Complex Traits Revealed by GWAS and Regional Heritability Mapping Analyses

Caballero, A., Tenesa, A., & Keightley, P. D. (2015) · Genetics · doi:10.1534/genetics.115.177220 · Cited by 59

Knowledge-Driven Multi-Locus Analysis Reveals Gene-Gene Interactions Influencing HDL Cholesterol Level in Two Independent EMR-Linked Biobanks

Turner, S., Berg, R. L., Linneman, J. G., Peissig, P. L., Crawford, D. C., Denny, J. C., Roden, D. M., McCarty, C. A., Ritchie, M. D., & Wilke, R. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019586 · Cited by 63

Development of GMDR-GPU for Gene-Gene Interaction Analysis and Its Application to WTCCC GWAS Data for Type 2 Diabetes

Zhu, Z., Tong, X., Zhu, Z., Liang, M., Cui, W., Su, K., Li, M. D., & Zhu, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061943 · Cited by 59

Invited review: Quantitative trait nucleotide determination in the era of genomic selection

Weller, J. I., & Ron, M. (2011) · Journal of Dairy Science · doi:10.3168/jds.2010-3793 · Cited by 59

A genome-wide gene-environment interaction analysis for tobacco smoke and lung cancer susceptibility

Zhang, R., Chu, M., Zhao, Y., Wu, C. H., Guo, H., Shi, Y., Dai, J., Wei, Y., Jin, G., Ma, H., et al. (2014) · Carcinogenesis · doi:10.1093/carcin/bgu076 · Cited by 63

A genome-wide association study for genetic susceptibility to Mycobacterium bovis infection in dairy cattle identifies a susceptibility QTL on chromosome 23

Richardson, I. W., Berry, D. P., Wiencko, H. L., Higgins, I., More, S. J., McClure, J. C., Lynn, D. J., & Bradley, D. G. (2016) · Genetics Selection Evolution · doi:10.1186/s12711-016-0197-x · Cited by 59

Identification of QTL for UV-Protective Eye Area Pigmentation in Cattle by Progeny Phenotyping and Genome-Wide Association Analysis

Pausch, H., Wang, X., Jung, S., Krogmeier, D., Edel, C., Emmerling, R., Götz, K., & Fries, R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036346 · Cited by 64

Ubiquitous Polygenicity of Human Complex Traits: Genome-Wide Analysis of 49 Traits in Koreans

Yang, J., Lee, T., Kim, J., Cho, M., Han, B., Lee, J., Lee, H. J., Cho, S., & Kim, H. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003355 · Cited by 62

Systems Biology Approaches and Applications in Obesity, Diabetes, and Cardiovascular Diseases

Meng, Q., Mäkinen, V., Luk, H., & Yang, X. (2012) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-012-0280-y · Cited by 58

Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations

Ding, L., Abebe, T., Beyene, J., Wilke, R. A., Goldberg, A., Woo, J. G., Martin, L. J., Rothenberg, M. E., Rao, M. B., Hershey, G. K. K., et al. (2013) · Human Genomics · doi:10.1186/1479-7364-7-16 · Cited by 61

High-throughput analysis of epistasis in genome-wide association studies with BiForce

Gyenesei, A., Moody, J., Semple, C. A. M., Haley, C., & Wei, W. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts304 · Cited by 61

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