Fejzo, M. S. et al. Nausea and vomiting of pregnancy and hyperemesis gravidarum. Nat. Rev. Dis. Primers 5, 62 (2019).
Wang, H. et al. Severe nausea and vomiting in pregnancy: psychiatric and cognitive problems and brain structure in children. BMC Med. 18, 228 (2020).
Gazmararian, J. Hospitalizations during pregnancy among managed care enrollees. Obstet. Gynecol. 100, 94–100 (2002).
Nana, M. et al. Termination of wanted pregnancy and suicidal ideation in hyperemesis gravidarum: a mixed methods study. Obstet. Med. 15, 180–184 (2022).
Munk-Olsen, T. et al. Postpartum depression: a developed and validated model predicting individual risk in new mothers. Transl. Psychiatry 12, 419 (2022).
Fejzo, M. S. Hyperemesis gravidarum theories dispelled by recent research: a paradigm change for better care and outcomes. Trends Mol. Med. 30, 530–540 (2024).
Almond, D., Edlund, L., Joffe, M. & Palme, M. An adaptive significance of morning sickness? Trivers–Willard and hyperemesis gravidarum. Econ. Hum. Biol. 21, 167–171 (2016).
Sasso, E. B. et al. Marijuana use and perinatal outcomes in obstetric patients at a safety net hospital. Eur. J. Obstet. Gynecol. Reprod. Biol. 266, 36–41 (2021).
First, O. K. et al. Patterns of use and self-reported effectiveness of cannabis for hyperemesis gravidarum. Geburtshilfe Frauenheilkd. 82, 517–527 (2022).
Fejzo, M. S. et al. Placenta and appetite genes GDF15 and IGFBP7 are associated with hyperemesis gravidarum. Nat. Commun. 9, 1178 (2018).
Fejzo, M. S., MacGibbon, K. W., First, O., Quan, C. & Mullin, P. M. Whole-exome sequencing uncovers new variants in GDF15 associated with hyperemesis gravidarum. BJOG 129, 1845–1852 (2022).
Fejzo, M., MacGibbon, K. & Mullin, P. 905: Hormone receptor genes PGR and GFRAL linked to hyperemesis gravidarum. Am. J. Obstet. Gynecol. 220, S585–S586 (2019).
Gottesman, O. et al. The Electronic Medical Records and Genomics (eMERGE) network: past, present, and future. Genet. Med. 15, 761–771 (2013).
Leitsalu, L. et al. Cohort profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int. J. Epidemiol. 44, 1137–1147 (2015).
Sudlow, C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Finer, S. et al. Cohort Profile: East London Genes & Health (ELGH), a community-based population genomics and health study in British Bangladeshi and British Pakistani people. Int. J. Epidemiol. 49, 20–21i (2020).
Access Results (FinnGen, accessed 9 January 2023); https://www.finngen.fi/en/access_results
Brumpton, B. M. et al. The HUNT study: a population-based cohort for genetic research. Cell Genom. 2, 100193 (2022).
Brandlistuen, R. E. et al. Cohort profile update: the Norwegian mother, father and child cohort (MoBa). Int. J. Epidemiol. 54, 382–388 (2025).
Zou, Y., Carbonetto, P., Wang, G. & Stephens, M. Fine-mapping from summary data with the ‘Sum of Single Effects’ model. PLoS Genet. 18, e1010299 (2022).
1000 Genomes Project Consortium et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
EGG Consortium et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat. Genet. 51, 804–814 (2019).
Fejzo, M. et al. GDF15 linked to maternal risk of nausea and vomiting during pregnancy. Nature 625, 760–767 (2024).
Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
Mansour, O. et al. Prescription medication use during pregnancy in the United States from 2011 to 2020: trends and safety evidence. Am. J. Obstet. Gynecol. 231, 250 (2024).
Gandal, M. J. et al. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362, eaat8127 (2018).
Gusev, A. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245–252 (2016).
Loesch, D. P. et al. Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities. Nat. Commun. 16, 2124 (2025).
Xu, Y. et al. An atlas of genetic scores to predict multi-omic traits. Nature 616, 123–131 (2023).
ENCODE Project Consortium et al. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583, 699–710 (2020).
Wang, M. et al. Single-nucleus multi-omic profiling of human placental syncytiotrophoblasts identifies cellular trajectories during pregnancy. Nat. Genet. 56, 294–305 (2024).
Luo, Y. et al. New developments on the Encyclopedia of DNA Elements (ENCODE) data portal. Nucleic Acids Res. 48, D882–D889 (2020).
ENCODE Project Consortium An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).
Ward, L. D. & Kellis, M. HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res. 44, D877–D881 (2016).
Buniello, A. et al. Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery. Nucleic Acids Res. 53, D1467–D1475 (2025).
Fiaschi, L., Nelson-Piercy, C., Gibson, J., Szatkowski, L. & Tata, L. J. Adverse maternal and birth outcomes in women admitted to hospital for hyperemesis gravidarum: a population-based cohort study. Paediatr. Perinat. Epidemiol. 32, 40–51 (2018).
Beaumont, R. N. et al. Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth. Nat. Genet. 55, 1807–1819 (2023).
Fejzo, M. S. et al. Symptoms and pregnancy outcomes associated with extreme weight loss among women with hyperemesis gravidarum. J. Womens Health (Larchmt) 18, 1981–1987 (2009).
Uhlén, M. et al. Proteomics. Tissue-based map of the human proteome. Science 347, 1260419 (2015).
Stilley, J. A. W. et al. FSH receptor (FSHR) expression in human extragonadal reproductive tissues and the developing placenta, and the impact of its deletion on pregnancy in mice. Biol. Reprod. 91, 74 (2014).
Yokokawa, T. et al. Influence of menopause on chemotherapy-induced nausea and vomiting in highly emetogenic chemotherapy for breast cancer: a retrospective observational study. Cancer Med. 12, 18745–18754 (2023).
Mbarek, H. et al. Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity. Hum. Reprod. 39, 240–257 (2024).
Bailit, J. L. Hyperemesis gravidarium: epidemiologic findings from a large cohort. Am. J. Obstet. Gynecol. 193, 811–814 (2005).
Michetti, C. et al. The knockout of synapsin II in mice impairs social behavior and functional connectivity generating an ASD-like phenotype. Cereb. Cortex 27, 5014–5023 (2017).
Hatayama, M. & Aruga, J. Developmental control of noradrenergic system by SLITRK1 and its implications in the pathophysiology of neuropsychiatric disorders. Front. Mol. Neurosci. 15, 1080739 (2023).
Jang, S. et al. Synaptic adhesion molecule IgSF11 regulates synaptic transmission and plasticity. Nat. Neurosci. 19, 84–93 (2016).
Moore, A., Linden, J. & Jentsch, J. D. Syn3gene knockout negatively impacts aspects of reversal learning performance. eNeuro 8, ENEURO.0251-21.2021 (2021).
Aonuma, H. et al. Effects of 5-HT and insulin on learning and memory formation in food-deprived snails. Neurobiol. Learn. Mem. 148, 20–29 (2018).
McCutcheon, J. E., Ebner, S. R., Loriaux, A. L. & Roitman, M. F. Encoding of aversion by dopamine and the nucleus accumbens. Front. Neurosci. 6, 137 (2012).
Hatayama, M. et al. SLITRK1-mediated noradrenergic projection suppression in the neonatal prefrontal cortex. Commun. Biol. 5, 935 (2022).
Fejzo, M. S. et al. Antihistamines and other prognostic factors for adverse outcome in hyperemesis gravidarum. Eur. J. Obstet. Gynecol. Reprod. Biol. 170, 71–76 (2013).
Wan, E. S. et al. Genome-wide association analysis of body mass in chronic obstructive pulmonary disease. Am. J. Respir. Cell Mol. Biol. 45, 304–310 (2011).
Groarke, J. D. et al. Phase 2 study of the efficacy and safety of ponsegromab in patients with cancer cachexia: PROACC-1 study design. J. Cachexia Sarcopenia Muscle 15, 1054–1061 (2024).
Suriben, R. et al. Antibody-mediated inhibition of GDF15–GFRAL activity reverses cancer cachexia in mice. Nat. Med. 26, 1264–1270 (2020).
Lee, J., Ng, K. G.-L., Dombek, K. M., Eom, D. S. & Kwon, Y. V. Tumors overcome the action of the wasting factor ImpL2 by locally elevating Wnt/Wingless. Proc. Natl Acad. Sci. USA 118, e2020120118 (2021).
Madeddu, C., Macciò, A., Panzone, F., Tanca, F. M. & Mantovani, G. Medroxyprogesterone acetate in the management of cancer cachexia. Expert Opin. Pharmacother. 10, 1359–1366 (2009).
Leong, M. L., Karjalainen, K. & Ruedl, C. TCF7L2 is a master regulator of muscle wasting in severe cancer cachexia. Preprint at Research Square https://doi.org/10.21203/rs.3.rs-2033935/v1 (2022).
Wylde, S., Nwose, E. & Bwititi, P. Morning sickness in pregnancy: mini review of possible causes with proposal for monitoring by diagnostic methods. Int. J. Reprod. Contracept. Obstet. Gynecol. 261, 267 (2016).
Zhou, Y. et al. TCF7L2 is a master regulator of insulin production and processing. Hum. Mol. Genet. 23, 6419–6431 (2014).
Kim, H., Takegahara, N. & Choi, Y. IgSF11-mediated phosphorylation of pyruvate kinase M2 regulates osteoclast differentiation and prevents pathological bone loss. Bone Res. 11, 17 (2023).
Cheng, Y. et al. Follicle-stimulating hormone orchestrates glucose-stimulated insulin secretion of pancreatic islets. Nat. Commun. 14, 6991 (2023).
Liu, Y. et al. Serum IGFBP7 levels associate with insulin resistance and the risk of metabolic syndrome in a Chinese population. Sci. Rep. 5, 10227 (2015).
Zhang, S.-Y., Danaei, Z., Bruce, K., Chiu, J. F. M. & Lam, T. K. T. Acute activation of GFRAL in the area postrema contributes to glucose regulation independent of weight. Diabetes 73, 426–433 (2024).
Gloria-Bottini, F. et al. Body mass index and acid phosphatase locus 1 in diabetic disorders. Acta Diabetol. 47, 139–143 (2010).
Huxley, R. Nausea and vomiting in early pregnancy: its role in placental development. Obstet. Gynecol. 95, 779–782 (2000).
Lee, S., Lee, C. E., Elias, C. F. & Elmquist, J. K. Expression of the diabetes-associated gene TCF7L2 in adult mouse brain. J. Comp. Neurol. 517, 925–939 (2009).
Maselli, D. et al. Effects of liraglutide on gastrointestinal functions and weight in obesity: a randomized clinical and pharmacogenomic trial. Obesity (Silver Spring) 30, 1608–1620 (2022).
Dowsett, G. K. C. et al. A survey of the mouse hindbrain in the fed and fasted states using single-nucleus RNA sequencing. Mol. Metab. 53, 101240 (2021).
Huang, X. et al. Gut hormone multi-agonists for the treatment of type 2 diabetes and obesity: advances and challenges. J. Endocrinol. 262, e230404 (2024).
Marsh, B. & Blelloch, R. Single nuclei RNA-seq of mouse placental labyrinth development. eLife 9, e60266 (2020).
Boj, S. F. et al. Diabetes risk gene and Wnt effector Tcf7l2/TCF4 controls hepatic response to perinatal and adult metabolic demand. Cell 151, 1595–1607 (2012).
Mulcahy, M. C. et al. GDF15 knockout does not substantially impact perinatal body weight or neonatal outcomes in mice. Endocrinology 165, bqae143 (2024).
Chatterjee, S. et al. Loss of Igfbp7 causes precocious involution in lactating mouse mammary gland. PLoS ONE 9, e87858 (2014).
Toufaily, C. et al. Impaired LH surge amplitude in gonadotrope-specific progesterone receptor knockout mice. J. Endocrinol. 244, 111–122 (2020).
McIntire, R. H. et al. Novel HLA-G-binding leukocyte immunoglobulin-like receptor (LILR) expression patterns in human placentas and umbilical cords. Placenta 29, 631–638 (2008).
Honigberg, M. C. et al. Polygenic prediction of preeclampsia and gestational hypertension. Nat. Med. 29, 1540–1549 (2023).
Wertaschnigg, D. et al. Second- and third-trimester serum levels of growth-differentiation factor-15 in prediction of pre-eclampsia. Ultrasound Obstet. Gynecol. 56, 879–884 (2020).
Yonezawa, Y. et al. Genome-wide association study of nausea and vomiting during pregnancy in Japan: the TMM BirThree Cohort Study. BMC Pregnancy Childbirth 24, 209 (2024).
Turner, S. D. qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. J. Open Source Softw. 3, 731 (2018).
Ochoa, D. et al. The next-generation Open Targets Platform: reimagined, redesigned, rebuilt. Nucleic Acids Res. 51, D1353–D1359 (2023).
Mbatchou, J. et al. Computationally efficient whole-genome regression for quantitative and binary traits. Nat. Genet. 53, 1097–1103 (2021).
Other Maternal Disorders Predominantly Related to Pregnancy (Risteys, accessed 9 January 2023); https://risteys.finregistry.fi/endpoints/O15_PREG_OTHER_MAT_DISORD
Pujol-Gualdo, N. et al. Advancing our understanding of genetic risk factors and potential personalized strategies for pelvic organ prolapse. Nat. Commun. 13, 3584 (2022).
Koel, M. et al. GWAS meta-analyses clarify the genetics of cervical phenotypes and inform risk stratification for cervical cancer. Hum. Mol. Genet. 32, 2103–2116 (2023).
Mitt, M. et al. Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel. Eur. J. Hum. Genet. 25, 869–876 (2017).
Åsvold, B. O. et al. Cohort profile update: the HUNT study, Norway. Int. J. Epidemiol. 52, e80–e91 (2023).
Wu, P. et al. Mapping ICD-10 and ICD-10-CM codes to phecodes: workflow development and initial evaluation. JMIR Med. Inform. 7, e14325 (2019).
Zuvich, R. L. et al. Pitfalls of merging GWAS data: lessons learned in the eMERGE network and quality control procedures to maintain high data quality. Genet. Epidemiol. 35, 887–898 (2011).
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
Magnus, P. et al. Cohort profile update: the Norwegian mother and child cohort study (MoBa). Int. J. Epidemiol. 45, 382–388 (2016).
The Bioconda Team et al. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat. Methods 15, 475–476 (2018).
Mölder, F. et al. Sustainable data analysis with Snakemake. F1000Res. 10, 33 (2021).
Sherry, S. T., Ward, M. & Sirotkin, K. DbSNP—database for single nucleotide polymorphisms and other classes of minor genetic variation. Genome Res. 9, 677–679 (1999).
Schneider, V. A. et al. Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly. Genome Res. 27, 849–864 (2017).
Murphy, A. E., Schilder, B. M. & Skene, N. G. MungeSumstats: a Bioconductor package for the standardization and quality control of many GWAS summary statistics. Bioinformatics 37, 4593–4596 (2021).
Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Wang, G., Sarkar, A., Carbonetto, P. & Stephens, M. A simple new approach to variable selection in regression, with application to genetic fine mapping. J. R. Stat. Soc. Series B Stat. Methodol. 82, 1273–1300 (2020).
Fairley, S., Lowy-Gallego, E., Perry, E. & Flicek, P. The International Genome Sample Resource (IGSR) collection of open human genomic variation resources. Nucleic Acids Res. 48, D941–D947 (2020).
The International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).
Greenbaum, S. et al. A spatially resolved timeline of the human maternal–fetal interface. Nature 619, 595–605 (2023).
Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
Huang, L. et al. TOP-LD: a tool to explore linkage disequilibrium with TOPMed whole-genome sequence data. Am. J. Hum. Genet. 109, 1175–1181 (2022).
Fejzo, M., Vaudel, M., Shu, C. & Mancuso, N. Multi-ancestry GWAS of severe pregnancy nausea and vomiting identifies risk loci associated with appetite, insulin signaling, and brain plasticity. Zenodo https://doi.org/10.5281/zenodo.18274564 (2026).
Vaudel, M. mvaudel/hyperemesis_gravidarum: publication. Zenodo https://doi.org/10.5281/zenodo.18675025 (2026).