Yaghootkar, Hanieh

Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis

Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Kasela, S., et al. (2018) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 2,607

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Yazar, S., et al. (2021) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 2,607

Systematic identification of trans eQTLs as putative drivers of known disease associations

Westra, H.-J., Peters, M. J., Esko, T., Yaghootkar, H., Schurmann, C., Kettunen, J., Christiansen, M. W., Fairfax, B. P., Schramm, K., Powell, J. E., et al. (2013) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 1,658

The transcriptional landscape of age in human peripheral blood

Peters, M. J., Joehanes, R., Pilling, L. C., Schurmann, C., Conneely, K. N., Powell, J., Reinmaa, E., Sutphin, G. L., Zhernakova, A., Schramm, K., et al. (2015) · Nature Communications

Genetics, Aging, and Longevity in Model OrganismsEpigenetics and DNA Methylation

Cited by 725

Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms

Jones, S. E., Lane, J. M., Wood, A. R., van Hees, V. T., Tyrrell, J., Beaumont, R. N., Jeffries, A. R., Dashti, H. S., Hillsdon, M., Ruth, K. S., et al. (2019) · Nature Communications

Circadian rhythm and melatoninGenetic Associations and Epidemiology

Cited by 691

Rare and low-frequency coding variants alter human adult height

Marouli, E., Graff, M., Medina-Gomez, C., Lo, K. S., Wood, A. R., Kjaer, T. R., Fine, R. S., Lu, Y., Schurmann, C., Highland, H. M., et al. (2017) · Nature

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 610

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Mahajan, A., Wessel, J., Willems, S. M., Zhao, W., Robertson, N. R., Chu, A. Y., Gan, W., Kitajima, H., Taliun, D., Rayner, N. W., et al. (2018) · Nature Genetics

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 442

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Qi, T., Wu, Y., Zeng, J., Zhang, F., Xue, A., Jiang, L., Zhu, Z., Kemper, K., Yengo, L., Zheng, Z., et al. (2018) · Nature Communications

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 427

Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci

Jones, S. E., Tyrrell, J., Wood, A. R., Beaumont, R. N., Ruth, K. S., Tuke, M. A., Yaghootkar, H., Hu, Y., Teder-Laving, M., Hayward, C., et al. (2016) · PLOS Genetics

Circadian rhythm and melatoninGenetic Associations and Epidemiology

Cited by 388

Height, body mass index, and socioeconomic status: mendelian randomisation study in UK Biobank

Tyrrell, J., Jones, S. E., Beaumont, R., Astley, C. M., Lovell, R., Yaghootkar, H., Tuke, M., Ruth, K. S., Freathy, R. M., Hirschhorn, J. N., et al. (2016) · BMJ

Genetic Associations and EpidemiologyIntergenerational and Educational Inequality Studies

Cited by 372

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits.

Porcu, E., Rüeger, S., Lepik, K., eQTLGen Consortium, Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., et al. (2019) · Nature Communications

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 322

Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension

CHARGE-Heart Failure Consortium, Surendran, P., EchoGen Consortium, METASTROKE Consortium, GIANT Consortium, EPIC-InterAct Consortium, Study, L. C., Wellcome Trust Case Control Consortium, Understanding Society Scientific Group, EPIC-CVD Consortium, et al. (2016) · Nature Genetics

Genetic Associations and EpidemiologyBlood Pressure and Hypertension Studies

Cited by 312

New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism

The Meta-Analyses of Glucose- and Insulin-related traits Consortium (MAGIC), Horikoshi, M., Early Growth Genetics (EGG) Consortium, Yaghootkar, H., Mook-Kanamori, D. O., Sovio, U., Taal, H. R., Hennig, B. J., Bradfield, J. P., St Pourcain, B., et al. (2013) · Nature Genetics

Birth, Development, and HealthGenetic Associations and Epidemiology

Cited by 309

Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour

Jones, S. E., van Hees, V. T., Mazzotti, D. R., Marques-Vidal, P., Sabia, S., van der Spek, A., Dashti, H. S., Engmann, J., Kocevska, D., Tyrrell, J., et al. (2019) · Nature Communications

Sleep and related disordersGenetic Associations and Epidemiology

Cited by 300

A Common Allele in FGF21 Associated with Sugar Intake Is Associated with Body Shape, Lower Total Body-Fat Percentage, and Higher Blood Pressure

Frayling, T. M., Beaumont, R. N., Jones, S. E., Yaghootkar, H., Tuke, M. A., Ruth, K. S., Casanova, F., West, B., Locke, J., Sharp, S., et al. (2018) · Cell Reports

Fibroblast Growth Factor ResearchGenetic Associations and Epidemiology

Cited by 101

Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively

The GIANT consortium, Wood, A. R., Tyrrell, J., Beaumont, R., Jones, S. E., Tuke, M. A., Ruth, K. S., Yaghootkar, H., Freathy, R. M., Murray, A., et al. (2016) · Diabetologia

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 74

Genetic evidence that lower circulating FSH levels lengthen menstrual cycle, increase age at menopause and impact female reproductive health

Ruth, K. S., Beaumont, R. N., Tyrrell, J., Jones, S. E., Tuke, M. A., Yaghootkar, H., Wood, A. R., Freathy, R. M., Weedon, M. N., Frayling, T. M., et al. (2016) · Human Reproduction

Hypothalamic control of reproductive hormonesReproductive Biology and Fertility

Cited by 70

Disease consequences of higher adiposity uncoupled from its adverse metabolic effects using Mendelian randomisation

Martin, S., Tyrrell, J., Thomas, E. L., Bown, M. J., Wood, A. R., Beaumont, R. N., Tsoi, L. C., Stuart, P. E., Elder, J. T., Law, P., et al. (2022) · eLife

Genetic Associations and EpidemiologyAdipokines, Inflammation, and Metabolic Diseases

Cited by 43

Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

Jones, S. E., Hees, V. T. V., Mazzotti, D. R., Marques-Vidal, P., Sabia, S., der Spek, A. V., Dashti, H. S., Engmann, J., Kocevska, D., Tyrrell, J., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory)

Sleep and related disordersGenetic Associations and Epidemiology

Cited by 14

Genetic evidence strongly supports managing weight and blood pressure in addition to glycemic control in preventing vascular complications in people with type 2 diabetes

Ahmed, A., Amin, H., Drenos, F., Sattar, N., & Yaghootkar, H. (2023) · Diabetes Care

Genetic Associations and EpidemiologyDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 10

Advancing a causal role of type 2 diabetes and its components in developing macro- and microvascular complications via genetic studies

Ahmed, A., Sattar, N., & Yaghootkar, H. (2022) · Diabetic Medicine

Genetic Associations and EpidemiologyDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 10