Multivariate genome-wide analyses of the well-being spectrum

The satisfaction with life scale

Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985) · Journal of Personality Assessment · doi:10.1207/s15327752jpa4901_13 · Cited by 31,768

Conducting Meta-Analyses in R with the metafor Package

Viechtbauer, W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i03 · Cited by 20,464

An integrated map of genetic variation from 1,092 human genomes

The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711

Biological insights from 108 schizophrenia-associated genetic loci

Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577

Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.

Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110

LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559

The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): development and UK validation

Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., Parkinson, J., Secker, J., & Stewart-Brown, S. (2007) · Health and Quality of Life Outcomes · doi:10.1186/1477-7525-5-63 · Cited by 5,031

An atlas of genetic correlations across human diseases and traits

ReproGen Consortium, Bulik-Sullivan, B., Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., Duncan, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3406 · Cited by 4,255

A Measure of Subjective Happiness: Preliminary Reliability and Construct Validation

Lyubomirsky, S., & Lepper, H. S. (1999) · Social Indicators Research · doi:10.1023/a:1006824100041 · Cited by 4,071

10 Years of GWAS Discovery: Biology, Function, and Translation

Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719

Genome-wide association studies

Uffelmann, E., Huang, Q. Q., Munung, N. S., de Vries, J., Okada, Y., Martin, A. R., Martin, H. C., Lappalainen, T., & Posthuma, D. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00056-9 · Cited by 1,849

Multi-trait analysis of genome-wide association summary statistics using MTAG

23andMe Research Team, Turley, P., Social Science Genetic Association Consortium, Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., Nguyen-Viet, T. A., Wedow, R., et al. (2018) · Nature Genetics · doi:10.1038/s41588-017-0009-4 · Cited by 1,112

Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits

Grotzinger, A. D., Rhemtulla, M., de Vlaming, R., Ritchie, S. J., Mallard, T. T., Hill, W. D., Ip, H. F., Marioni, R. E., McIntosh, A. M., Deary, I. J., et al. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0566-x · Cited by 958

Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions

Levey, D. F., Stein, M. B., Wendt, F. R., Pathak, G. A., Zhou, H., Aslan, M., Quaden, R., Harrington, K. M., Nuñez, Y. Z., Overstreet, C., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00860-2 · Cited by 422

Genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic and molecular genetic levels of analysis

Grotzinger, A. D., Mallard, T. T., Akingbuwa, W. A., Ip, H. F., Adams, M. J., Lewis, C. M., McIntosh, A. M., Grove, J., Dalsgaard, S., Lesch, K., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01057-4 · Cited by 340

Deconstructing the sources of genotype-phenotype associations in humans

Young, A. I., Benonisdottir, S., Przeworski, M., & Kong, A. (2019) · Science · doi:10.1126/science.aax3710 · Cited by 288

Genetic analyses identify widespread sex-differential participation bias

Pirastu, N., Cordioli, M., Nandakumar, P., Mignogna, G., Abdellaoui, A., Hollis, B., Kanai, M., Rajagopal, V. M., Parolo, P. D. B., Baya, N., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00846-7 · Cited by 251

A powerful method for pleiotropic analysis under composite null hypothesis identifies novel shared loci between Type 2 Diabetes and Prostate Cancer

Ray, D., & Chatterjee, N. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009218 · Cited by 242

Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images

Zhao, B., Li, T., Fan, Z., Yang, Y., Shu, J., Yang, X., Wang, X., Luo, T., Tang, J., Xiong, D., et al. (2023) · Science · doi:10.1126/science.abn6598 · Cited by 235

Common genetic variation influencing human white matter microstructure

Zhao, B., Li, T., Yang, Y., Wang, X., Luo, T., Shan, Y., Zhu, Z., Xiong, D., Hauberg, M. E., Bendl, J. M., et al. (2021) · Science · doi:10.1126/science.abf3736 · Cited by 222

The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

Coleman, J. R. I., Gaspar, H. A., Bryois, J., Byrne, E. M., Forstner, A. J., Holmans, P. A., de Leeuw, C. A., Mattheisen, M., McQuillin, A., Whitehead Pavlides, J. M., et al. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.10.015 · Cited by 199

Multi-polygenic score approach to trait prediction

Krapohl, E. M. L., Patel, H., Newhouse, S., Curtis, C. J. C., von Stumm, S., Dale, P. S., Zabaneh, D., Breen, G. D., O’Reilly, P. F., & Plomin, R. J. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.163 · Cited by 196

Using genetics for social science

Harden, K. P., & Koellinger, P. D. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0862-5 · Cited by 180

Sociology, Genetics, and the Coming of Age of Sociogenomics

Mills, M. C., & Tropf, F. C. (2020) · Annual Review of Sociology · doi:10.1146/annurev-soc-121919-054756 · Cited by 162

Common variants contribute to intrinsic human brain functional networks

Zhao, B., Li, T., Smith, S. M., Xiong, D., Wang, X., Yang, Y., Luo, T., Zhu, Z., Shan, Y., Matoba, N., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01039-6 · Cited by 150

Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure

Levin, M. G., Tsao, N. L., Singhal, P., Liu, C., Vy, H. M. T., Paranjpe, I., Backman, J., Bellomo, T. R., Bone, W. P., Biddinger, K. J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34216-6 · Cited by 155

Causal influences of neuroticism on mental health and cardiovascular disease

Zhang, F., Baranova, A. V., Zhou, C., Cao, H., Chen, J., Zhang, X., & Xu, M. (2021) · Human Genetics · doi:10.1007/s00439-021-02288-x · Cited by 144

Symptom-level modelling unravels the shared genetic architecture of anxiety and depression

Thorp, J. G., Campos, A. I., Grotzinger, A. D., Gerring, Z. F., An, J., Ong, J., Wang, W., Shringarpure, S., Byrne, E. M., MacGregor, S., et al. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01094-9 · Cited by 110

Identifying loci with different allele frequencies among cases of eight psychiatric disorders using CC-GWAS

Peyrot, W. J., & Price, A. L. (2021) · Nature Genetics · doi:10.1038/s41588-021-00787-1 · Cited by 107

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

Abdellaoui, A., Sanchez‐Roige, S., Sealock, J., Treur, J. L., Dennis, J. K., Fontanillas, P., Elson, S. L., Nivard, M. G., Ip, H. F., van der Zee, M. D., et al. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz219 · Cited by 106

Genomics and psychological resilience: a research agenda

Choi, K. W., Stein, M. B., Dunn, E. C., Koenen, K. C., & Smoller, J. W. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0457-6 · Cited by 108

Genome-wide analyses identify 30 loci associated with obsessive–compulsive disorder

Strom, N. I., Gerring, Z. F., Galimberti, M., Yu, D., Halvorsen, M., Abdellaoui, A., Rodriguez‐Fontenla, C., Sealock, J., Bigdeli, T. B., Coleman, J. R. I., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02189-z · Cited by 123

Dissecting polygenic signals from genome-wide association studies on human behaviour

Abdellaoui, A., & Verweij, K. J. H. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01110-y · Cited by 104

Acquired risk factors and incident atrial fibrillation according to age and genetic predisposition

Wang, N., Yu, Y., Sun, Y. B., Zhang, H., Wang, Y., Chen, C., Tan, X. W., Wang, B., & Lu, Y. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehad615 · Cited by 96

The Parkinson's Disease Genome‐Wide Association Study Locus Browser

Grenn, F. P., Kim, J. J., Makarious, M. B., Iwaki, H., Illarionova, A., Brolin, K., Kluss, J. H., Schumacher‐Schuh, A. F., Leonard, H., Faghri, F., et al. (2020) · Movement Disorders · doi:10.1002/mds.28197 · Cited by 92

Eye-brain connections revealed by multimodal retinal and brain imaging genetics

Zhao, B., Li, Y., Fan, Z., Wu, Z., Shu, J., Yang, X., Yang, Y., Wang, X., Li, B., Wang, X., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50309-w · Cited by 92

Comprehensive exploration of the genetic contribution of the dopaminergic and serotonergic pathways to psychiatric disorders

Cabana‐Domínguez, J., Torrico, B., Reif, A., Fernàndez‐Castillo, N., & Cormand, B. (2022) · Translational Psychiatry · doi:10.1038/s41398-021-01771-3 · Cited by 87

A genetic perspective on the relationship between eudaimonic –and hedonic well-being

Baselmans, B. M. L., & Bartels, M. (2018) · Scientific Reports · doi:10.1038/s41598-018-32638-1 · Cited by 88

Integrative analysis of genome-wide association studies identifies novel loci associated with neuropsychiatric disorders

Yao, X., Glessner, J., Li, J., Qi, X., Hou, X., Zhu, C., Li, X., March, M., Yang, L., Mentch, F. D., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-020-01195-5 · Cited by 82

The human physiology of well-being: A systematic review on the association between neurotransmitters, hormones, inflammatory markers, the microbiome and well-being

de Vries, L. P., van de Weijer, M. P., & Bartels, M. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104733 · Cited by 85

Identification of shared and differentiating genetic architecture for autism spectrum disorder, attention-deficit hyperactivity disorder and case subgroups

Mattheisen, M., Grove, J., Als, T. D., Martin, J., Voloudakis, G., Meier, S. M., Demontis, D., Bendl, J. M., Walters, R. K., Carey, C. E., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01171-3 · Cited by 80

Large-scale genome sequencing redefines the genetic footprints of high-altitude adaptation in Tibetans

Zheng, W., He, Y., Guo, Y., Yue, T., Zhang, H., Li, J., Zhou, B., Zeng, X., Li, L., Wang, B., et al. (2023) · Genome biology · doi:10.1186/s13059-023-02912-1 · Cited by 81

Multi-PGS enhances polygenic prediction by combining 937 polygenic scores

Albiñana, C., Zhu, Z., Schork, A. J., Ingason, A., Aschard, H., Brikell, I., Bulik, C. M., Petersen, L. V., Agerbo, E., Grove, J., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40330-w · Cited by 84

Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction

Schormair, B., Zhao, C., Bell, S., Didriksen, M., Nawaz, M. S., Schandra, N., Stefani, A., Högl, B., Dauvilliers, Y. A., Bachmann, C. G., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01763-1 · Cited by 79

CADM2 is implicated in impulsive personality and numerous other traits by genome- and phenome-wide association studies in humans and mice

Sanchez‐Roige, S., Jennings, M. V., Thorpe, H. H. A., Mallari, J. E., van der Werf, L. C., Bianchi, S. B., Huang, Y., Lee, C., Mallard, T. T., Barnes, S. A., et al. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02453-y · Cited by 77

Genetic association study of childhood aggression across raters, instruments, and age

Ip, H. F., van der Laan, C. M., Krapohl, E. M. L., Brikell, I., Sánchez-Mora, C., Nolte, I. M., St Pourcain, B., Bolhuis, K., Palviainen, T., Zafarmand, H., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01480-x · Cited by 71

Higher polygenic risk scores for schizophrenia may be suggestive of treatment non-response in major depressive disorder

Fanelli, G., Benedetti, F., Kasper, S., Zohar, J., Souery, D., Montgomery, S., Albani, D., Forloni, G., Ferentinos, P. P., Rujescu, D., et al. (2020) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.110170 · Cited by 72

Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond

Gaddis, N., Mathur, R., Marks, J. A., Zhou, L., Quach, B. C., Waldrop, A., Levran, O., Arpana Agrawal, A., Randesi, M., Adelson, M., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-21003-y · Cited by 75

Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms

Jami, E. S., Hammerschlag, A. R., Ip, H. F., Allegrini, A. G., Benyamin, B., Border, R., Diemer, E. W., Jiang, C., Karhunen, V., Lu, Y., et al. (2022) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2021.11.035 · Cited by 73

Emerging phenotyping strategies will advance our understanding of psychiatric genetics

Sanchez‐Roige, S., & Palmer, A. A. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0609-7 · Cited by 74

Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration

Austin-Zimmerman, I., Levey, D. F., Giannakopoulou, O., Deak, J. D., Galimberti, M., Adhikari, K., Zhou, H., Denaxas, S., Irizar, H., Kuchenbaecker, K. B., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41249-y · Cited by 67

A Genetic Investigation of the Well-Being Spectrum

Baselmans, B. M. L., van de Weijer, M. P., Abdellaoui, A., Vink, J. M., Hottenga, J., Willemsen, G. A. H. M., Nivard, M. G., de Geus, E. J. C., Boomsma, D. I., & Bartels, M. (2019) · Behavior Genetics · doi:10.1007/s10519-019-09951-0 · Cited by 69

How Natural Genetic Variation Shapes Behavior

Niepoth, N., & Bendesky, A. (2020) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-111219-080427 · Cited by 61

Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder

Dahl, A., Thompson, M., An, U., Krebs, M. D., Appadurai, V., Border, R., Bacanu, S., Werge, T. M., Flint, J., Schork, A. J., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01559-9 · Cited by 63

Molecular genetics in psychology and personality neuroscience: On candidate genes, genome wide scans, and new research strategies

Montag, C., Ebstein, R. P., Jawinski, P., & Markett, S. A. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.06.020 · Cited by 58

Genetic Data: Potential Uses and Misuses in Marketing

Daviet, R., Nave, G., & Wind, J. Y. (2020) · Journal of Marketing · doi:10.1177/0022242920980767 · Cited by 59

Multi-trait transcriptome-wide association studies with probabilistic Mendelian randomization

Liu, L., Zeng, P., Xue, F., Yuan, Z., & Zhou, X. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.12.006 · Cited by 52

Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology

Milind, N., Preuß, C., Haber, A., Ananda, G., Mukherjee, S., Cai, J., Shapley, S. M., Tyler, A. L., Logsdon, B. A., Crane, P. K., et al. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1008775 · Cited by 51

General dimensions of human brain morphometry inferred from genome‐wide association data

Fürtjes, A. E., Arathimos, R., Coleman, J. R. I., Cole, J. H., Cox, S. R., Deary, I. J., de la Fuente, J., Madole, J. W., Tucker–Drob, E. M., & Ritchie, S. J. (2023) · Human Brain Mapping · doi:10.1002/hbm.26283 · Cited by 51

Paternal transgenerational epigenetic mechanisms mediating stress phenotypes of offspring

Cunningham, A. M., Walker, D. M., & Nestler, E. J. (2019) · European Journal of Neuroscience · doi:10.1111/ejn.14582 · Cited by 50

The genetic architecture of human brainstem structures and their involvement in common brain disorders

Elvsåshagen, T., Bahrami, S., van der Meer, D., Agartz, I., Alnæs, D., Barch, D. M., Baur‐Streubel, R., Bertolino, A., Beyer, M. K., Blasi, G., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17376-1 · Cited by 47

Further confirmation of netrin 1 receptor (DCC) as a depression risk gene via integrations of multi-omics data

Li, H., Qu, N., Hui, L., Cai, X. M., Zhang, C., Zhong, B., Zhang, S.-F., Chen, J., Xia, B., Wang, L., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0777-y · Cited by 44

Methylome-wide association study of antidepressant use in Generation Scotland and the Netherlands Twin Register implicates the innate immune system

Barbu, M. C., Huider, F., Campbell, A., Amador, C., Adams, M. J., Lynall, M.-E., Howard, D. M., Walker, R. M., Morris, S. W., Van Dongen, J., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-021-01412-7 · Cited by 43

Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being

de Vries, L. P., van Beijsterveldt, T. C. E. M., MAES, H. H. M., Colodro‐Conde, L., & Bartels, M. (2021) · Behavior Genetics · doi:10.1007/s10519-021-10046-y · Cited by 42

Synaptic and brain-expressed gene sets relate to the shared genetic risk across five psychiatric disorders

Hammerschlag, A. R., de Leeuw, C., Middeldorp, C. M., & Polderman, T. J. C. (2019) · Psychological Medicine · doi:10.1017/s0033291719001776 · Cited by 43

Quantitative Electroencephalogram (qEEG) as a Natural and Non-Invasive Window into Living Brain and Mind in the Functional Continuum of Healthy and Pathological Conditions

Fingelkurts, A. A., & Fingelkurts, A. A. (2022) · Applied Sciences · doi:10.3390/app12199560 · Cited by 43

The Genetic and Neural Substrates of Externalizing Behavior

Baselmans, B. M. L., Hammerschlag, A. R., Noordijk, S., Ip, H. F., van der Zee, M. D., de Geus, E. J. C., Abdellaoui, A., Treur, J. L., & Ent, D. V. ‘. (2021) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2021.09.007 · Cited by 43

The Role of Genetic Variation of BMI, Body Composition, and Fat Distribution for Mental Traits and Disorders: A Look-Up and Mendelian Randomization Study

Peters, T., Nüllig, L., Antel, J., Naaresh, R., Laabs, B., Tegeler, L., Amhaouach, C., Libuda, L., Hinney, A., & Hebebrand, J. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00373 · Cited by 36

Maternal environmental risk factors and the development of internalizing and externalizing problems in childhood: The complex role of genetic factors

Ensink, J. B. M., de Moor, M. H. M., Zafarmand, M. H., de Laat, S., Uitterlinden, A. G., Vrijkotte, T. G. M., Lindauer, R., & Middeldorp, C. M. (2019) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32755 · Cited by 35

Mendelian randomization evidence for the causal effect of mental well-being on healthy aging

Ye, C., Liu, D., Chen, M., Kong, L., Dou, C., Wang, Y.-Y., Xu, M., Xu, Y., Li, M., Zhao, Z., et al. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01905-9 · Cited by 36

Multitrait GWAS to connect disease variants and biological mechanisms

Julienne, H., Laville, V., McCaw, Z. R., He, Z., Guillemot, V., Lasry, C., Ziyatdinov, A., Nerin, C., Vaysse, A., Lechat, P., et al. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009713 · Cited by 35

Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy

Hindley, G., Shadrin, A. A., van der Meer, D., Parker, N., Cheng, W., O’Connell, K. S., Bahrami, S., Lin, A., Karadag, N., Holen, B., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01630-9 · Cited by 37

Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci

Mignogna, G., Carey, C. E., Wedow, R., Baya, N. A., Cordioli, M., Pirastu, N., Bellocco, R., Malerbi, K. F., Nivard, M. G., Neale, B. M., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01632-7 · Cited by 34

Methylome-wide change associated with response to electroconvulsive therapy in depressed patients

Sirignano, L., Frank, J., Kranaster, L., Witt, S. H., Streit, F., Zillich, L., Sartorius, A., Rietschel, M., & Foo, J. C. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01474-9 · Cited by 32

Causal Effects of Positive Affect, Life Satisfaction, Depressive Symptoms, and Neuroticism on Kidney Function: A Mendelian Randomization Study

Park, S., Lee, S., Kim, Y., Lee, Y., Kang, M. W., Kim, K., Kim, Y. C., Han, S. S., Lee, H., Lee, J. P., et al. (2021) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020071086 · Cited by 32

Integrate multiple traits to detect novel trait–gene association using GWAS summary data with an adaptive test approach

Guo, B., & Wu, B. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty961 · Cited by 33

Genetic evidence for a large overlap and potential bidirectional causal effects between resilience and well-being

de Vries, L. P., Baselmans, B. M. L., Luykx, J. J., de Zeeuw, E. L., Minică, C. C., de Geus, E. J. C., Vinkers, C. H., & Bartels, M. (2021) · Neurobiology of Stress · doi:10.1016/j.ynstr.2021.100315 · Cited by 33

An integrative multiomics analysis identifies putative causal genes for COVID-19 severity

Wu, L., Zhu, J., Liu, D., Sun, Y., & Wu, C. (2021) · Genetics in Medicine · doi:10.1038/s41436-021-01243-5 · Cited by 31

scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies

Jia, P., Hu, R., Yan, F., Dai, Y., & Zhao, Z. (2022) · Genome biology · doi:10.1186/s13059-022-02785-w · Cited by 32

MTAG: Multi-Trait Analysis of GWASPreprint

Turley, P., Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., Nguyen-Viet, T. A., Wedow, R., Zacher, M., Furlotte, N. A., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/118810 · Cited by 30

Diverse phenotypic measurements of wellbeing: Heritability, temporal stability and the variance explained by polygenic scores

Jamshidi, J., Williams, L. M., Schofield, P. R., Park, H. R. P., Montalto, A., Chilver, M. R., Bryant, R. A., Claudio Toma, A., Fullerton, J. M., & Gatt, J. M. (2020) · Genes Brain & Behavior · doi:10.1111/gbb.12694 · Cited by 31

Behavioral, Anatomical and Heritable Convergence of Affect and Cognition in Superior Frontal Cortex

Kraljević, N., Schaare, H. L., Eickhoff, S. B., Kochunov, P., Yeo, B. T. T., Masouleh, S. K., & Valk, S. L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118561 · Cited by 30

Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies

Schwabe, I., Milaneschi, Y., Gerring, Z. F., Sullivan, P. F., Schulte, E. C., Suppli, N. P., Thorp, J. G., Derks, E. M., & Middeldorp, C. M. (2019) · Psychological Medicine · doi:10.1017/s0033291719002502 · Cited by 34

Mapping anorexia nervosa genes to clinical phenotypes

Johnson, J., Cote, A. C., Dobbyn, A. L., Sloofman, L. G., Xu, J., Cotter, L., Charney, A. W., Birgegård, A., Jordan, J., Kennedy, M. A., et al. (2022) · Psychological Medicine · doi:10.1017/s0033291721004554 · Cited by 32

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology

Tan, V. Y., & Timpson, N. J. (2022) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-121321-093606 · Cited by 28

Virtues as protective factors for adolescent mental health

McLoughlin, S., & Kristjansson, K. R. (2024) · Journal of Research on Adolescence · doi:10.1111/jora.13004 · Cited by 34

Genome-wide association meta-analysis of childhood ADHD symptoms and diagnosis identifies new loci and potential effector genes

van der Laan, C. M., Ip, H. F., Schipper, M., Hottenga, J., Pourcain, B. S., Zayats, T., Pool, R., Krapohl, E. M. L., Brikell, I., Artigas, M. S., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02295-y · Cited by 32

A systematic review of the neural correlates of well-being reveals no consistent associations

de Vries, L. P., van de Weijer, M. P., & Bartels, M. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105036 · Cited by 29

Genome-wide association study identifies new locus associated with OCDPreprint

Strom, N. I., Yu, D., Gerring, Z. F., Halvorsen, M., Abdellaoui, A., Rodriguez‐Fontenla, C., Sealock, J., Bigdeli, T. B., Coleman, J. R. I., Mahjani, B., et al. (2021) · medRxiv · doi:10.1101/2021.10.13.21261078 · Cited by 28

The genetics of neuroticism: Insights from the Maudsley rat model and human studies

Blizard, D. A., Adams, N., & Boomsma, D. I. (2023) · Personality Neuroscience · doi:10.1017/pen.2023.4 · Cited by 26

Personality traits relate to chronotype at both the phenotypic and genetic level

Lenneis, A., Vainik, U., Teder‐Laving, M., Ausmees, L., Lemola, S., Allïk, J., & Realo, A. (2021) · Journal of Personality · doi:10.1111/jopy.12645 · Cited by 31

A Local Genetic Correlation Analysis Provides Biological Insights Into the Shared Genetic Architecture of Psychiatric and Substance Use Phenotypes

Gerring, Z. F., Thorp, J. G., Gamazon, E. R., & Derks, E. M. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.03.001 · Cited by 25

Phenotypic and genetic analysis of a wellbeing factor score in the UK Biobank and the impact of childhood maltreatment and psychiatric illness

Jamshidi, J., Schofield, P. R., Gatt, J. M., & Fullerton, J. M. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-01874-5 · Cited by 25

Happiness and well-being: The value and findings from genetic studies

van de Weijer, M. P., de Vries, L. P., & Bartels, M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-821514-2.00016-7 · Cited by 28

Integrative Multi-omics Analysis of Childhood Aggressive Behavior

Hagenbeek, F. A., van Dongen, J., Pool, R., Roetman, P. J., Harms, A. C., Hottenga, J., Kluft, C., Colins, O. F., van Beijsterveldt, C. E. M., Fanos, V., et al. (2022) · Behavior Genetics · doi:10.1007/s10519-022-10126-7 · Cited by 26

A splicing transcriptome-wide association study identifies novel altered splicing for Alzheimer's disease susceptibility

Sun, Y., Bae, Y. E., Zhu, J., Zhang, Z., Zhong, H., Yu, J., Wu, C., & Wu, L. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106209 · Cited by 25

Identification of candidate DNA methylation biomarkers related to Alzheimer’s disease risk by integrating genome and blood methylome data

Sun, Y., Zhu, J., Yang, Y., Zhang, Z., Zhong, H., Zeng, G., Zhou, D., Nowakowski, R. S., Long, J., Wu, C., et al. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02695-w · Cited by 25

Sensitive period-regulating genetic pathways and exposure to adversity shape risk for depression

Zhu, Y., Wang, M., Crawford, K. M., Ramírez-Tapia, J. C., Lussier, A. A., Davis, K. A., de Leeuw, C., Takesian, A. E., Hensch, T. K., Smoller, J. W., et al. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01172-6 · Cited by 26

The Architecture of Happiness

Lomas, T., Bartels, M., van de Weijer, M. P., Pluess, M., Hanson, J. A., & VanderWeele, T. J. (2022) · Emotion Review · doi:10.1177/17540739221114109 · Cited by 24

Integrative multi‐omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention‐Deficit /Hyperactivity Disorder

Hubers, N., Hagenbeek, F. A., Pool, R., Dejean, S., Harms, A. C., Roetman, P. J., van Beijsterveldt, C. E. M., Fanos, V., Ehli, E. A., Vermeiren, R. R. J. M., et al. (2023) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32955 · Cited by 26

A genome-wide association study of a rage-related misophonia symptom and the genetic link with audiological traits, psychiatric disorders, and personality

Smit, D. J. A., Bakker, M., Abdellaoui, A., Hoetink, A. E., Vulink, N. C. C., & Denys, D. A. J. P. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.971752 · Cited by 25

Identifying genetic loci and phenomic associations of substance use traits: A multi‐trait analysis of GWAS (MTAG) study

Xu, H. Y., Toikumo, S., Crist, R. C., Glogowska, K., Jinwala, Z., Deak, J. D., Justice, A. C., Gelernter, J. E., Johnson, E. C., Kranzler, H. R., et al. (2023) · Addiction · doi:10.1111/add.16229 · Cited by 23

Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain

Barowsky, S., Jung, J.-Y., Nesbit, N., Silberstein, M. D., D, M. F. M., Loggia, M. L., Smoller, J. W., & Lee, P. H. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.687687 · Cited by 23

Genome-wide association study of pain sensitivity assessed by questionnaire and the cold pressor test

Fontanillas, P., Kless, A., Bothmer, J., & Tung, J. Y. (2021) · Pain · doi:10.1097/j.pain.0000000000002568 · Cited by 23

Expanding the environmental scope: an environment-wide association study for mental well-being

van de Weijer, M. P., Baselmans, B. M. L., Hottenga, J., Dolan, C. V., Willemsen, G. A. H. M., & Bartels, M. (2021) · Journal of Exposure Science & Environmental Epidemiology · doi:10.1038/s41370-021-00346-0 · Cited by 25

Ultra-rare and common genetic variant analysis converge to implicate negative selection and neuronal processes in the aetiology of schizophrenia

Akingbuwa, W. A., Hammerschlag, A. R., Bartels, M., Nivard, M. G., & Middeldorp, C. M. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01621-8 · Cited by 22

Executive Function and Impulsivity Predict Distinct Genetic Variance in Internalizing Problems, Externalizing Problems, Thought Disorders, and Compulsive Disorders: A Genomic Structural Equation Modeling Study

Gustavson, D. E., Morrison, C. L., Mallard, T. T., Jennings, M. V., Fontanillas, P., Elson, S. L., Palmer, A. A., Friedman, N. P., & Sanchez‐Roige, S. (2023) · Clinical Psychological Science · doi:10.1177/21677026231207845 · Cited by 24

A genome-wide multiphenotypic association analysis identified common candidate genes for subjective well-being, depressive symptoms and neuroticism

Chu, X., Liu, L., Wen, Y. F., Li, P., Cheng, B., Cheng, S., Zhang, L., Ma, M., Qi, X., Liang, C., et al. (2020) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2020.02.012 · Cited by 21

Exploring the genetics of rhythmic perception and musical engagement in the Vanderbilt Online Musicality Study

Gustavson, D. E., Coleman, P. L., Wang, Y., Nitin, R., Petty, L. E., Bush, C. T., Mosing, M. A., Wesseldijk, L. W., Ullén, F., Below, J. E., et al. (2023) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14964 · Cited by 22

The goldmine of GWAS summary statistics: a systematic review of methods and tools

Kontou, P. I., & Bagos, P. G. (2024) · BioData Mining · doi:10.1186/s13040-024-00385-x · Cited by 23

Multivariate Genome-wide and integrated transcriptome and epigenome-wide analyses of the Well-being spectrumPreprint

Baselmans, B. M. L., Jansen, R., Ip, H. F., van Dongen, J., Abdellaoui, A., van de Weijer, M. P., Bao, Y., Smart, M., Meena Kumari, B., Willemsen, G. A. H. M., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/115915 · Cited by 9

Multi-trait analysis of genome-wide association summary statistics using MTAG

23andMe Research Team, Turley, P., Social Science Genetic Association Consortium, Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., Nguyen-Viet, T. A., Wedow, R., et al. (2018) · Nature Genetics · doi:10.1038/s41588-017-0009-4 · Cited by 1,112

Meta-Analysis of Genome-Wide Association Studies with Multivariate Traits

Cichońska, A., Marttinen, P., Ripatti, S., Rousu, J., & Pirinen, M. (2014)

MTAG: Multi-Trait Analysis of GWASPreprint

Turley, P., Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., Nguyen-Viet, T. A., Wedow, R., Zacher, M., Furlotte, N. A., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/118810 · Cited by 30

GWAS on happiness, satisfaction with life and overall well-beingPreprint

Okbay, A. (2013) · OSF Preprints (OSF Preprints)