Suzuki, K. et al. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature 627, 347–357 (2024).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Zhou, W. et al. Global Biobank Meta-analysis Initiative: powering genetic discovery across human disease. Cell Genom. 2, 100192 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Yengo, L. et al. A saturated map of common genetic variants associated with human height. Nature 610, 704–712 (2022).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

COVID-19 Host Genetics Initiative A second update on mapping the human genetic architecture of COVID-19. Nature 621, E7–E26 (2023).

Article 

Google Scholar
 

Aragam, K. G. et al. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants. Nat. Genet. 54, 1803–1815 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Lotta, L. A. et al. Genetic predisposition to an impaired metabolism of the branched-chain amino acids and risk of type 2 diabetes: a Mendelian randomisation analysis. PLoS Med. 13, e1002179 (2016).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Vanweert, F., Schrauwen, P. & Phielix, E. Role of branched-chain amino acid metabolism in the pathogenesis of obesity and type 2 diabetes-related metabolic disturbances BCAA metabolism in type 2 diabetes. Nutr. Diabetes 12, 35 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Karjalainen, M. K. et al. Genome-wide characterization of circulating metabolic biomarkers. Nature 628, 130–138 (2024).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Richardson, T. G. et al. Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation. PLoS Biol. 20, e3001547 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Smith, C. J. et al. Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation. eLife 11, e79348 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Rahu, I., Tambets, R., Fauman, E. B. & Alasoo, K. Mendelian randomization with proxy exposures: challenges and opportunities. Genetics 231, iyaf210 (2025).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

van der Meer, D. et al. Pleiotropic and sex-specific genetic mechanisms of circulating metabolic markers. Nat. Commun. 16, 4961 (2025).

Article 
ADS 
PubMed 
PubMed Central 

Google Scholar
 

Zoodsma, M. et al. A genetic map of human metabolism across the allele frequency spectrum. Nat. Genet. 57, 2445–2455 (2025).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Graham, S. E. et al. The power of genetic diversity in genome-wide association studies of lipids. Nature 600, 675–679 (2021).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Nag, A. et al. Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank. Am. J. Hum. Genet. 110, 487–498 (2023).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Sanderson, E. et al. Mendelian randomization. Nat. Rev. Methods Primers 2, 1–21 (2022).

Article 

Google Scholar
 

Stender, S., Gellert-Kristensen, H. & Smith, G. D. Reclaiming mendelian randomization from the deluge of papers and misleading findings. Lipids Health Dis. 23, 286 (2024).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Burgess, S., Woolf, B., Mason, A. M., Ala-Korpela, M. & Gill, D. Addressing the credibility crisis in Mendelian randomization. BMC Med. 22, 374 (2024).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Karczewski, K. J. et al. Pan-UK Biobank genome-wide association analyses enhance discovery and resolution of ancestry-enriched effects. Nat. Genet. 57, 2408–2417 (2025).

Article 
CAS 
PubMed 

Google Scholar
 

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).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Shi, S. et al. A Genomics England haplotype reference panel and imputation of UK Biobank. Nat. Genet. 56, 1800–1803 (2024).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Taliun, D. et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature 590, 290–299 (2021).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Kanai, M. et al. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution. Cell Genom. 2, 100210 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Jaganathan, K. et al. Predicting splicing from primary sequence with deep learning. Cell 176, 535–548.e24 (2019).

Article 
ADS 
CAS 
PubMed 

Google Scholar
 

Avsec, Ž et al. Advancing regulatory variant effect prediction with AlphaGenome. Nature 649, 1206–1218 (2026).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Jesse, M., Riet, A.-E. & Alasoo, K. Ultra-fast genetic colocalisation across millions of traits. Preprint at bioRxiv https://doi.org/10.1101/2025.08.25.672103 (2025).

Takeuchi, Y. et al. Genetic architecture of circulating metabolic biomarkers across ancestral populations. Preprint at medRxiv https://doi.org/10.64898/2025.12.03.25341540 (2025).

Kurki, M. I. et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 613, 508–518 (2023).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Verma, A. et al. Diversity and scale: genetic architecture of 2068 traits in the VA Million Veteran Program. Science 385, eadj1182 (2024).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Kerimov, N. et al. eQTL Catalogue 2023: new datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs. PLoS Genet. 19, e1010932 (2023).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Tokolyi, A. et al. The contribution of genetic determinants of blood gene expression and splicing to molecular phenotypes and health outcomes. Nat. Genet. 57, 616–625 (2025).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature 622, 329–338 (2023).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Momozawa, Y. et al. IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes. Nat. Commun. 9, 2427 (2018).

Article 
ADS 
PubMed 
PubMed Central 

Google Scholar
 

Akbari, P. et al. A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology. Nat. Commun. 14, 5023 (2023).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Buniello, A. et al. Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery. Nucleic Acids Res. 53, D1467–D1475 (2025).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Downes, K. et al. G protein-coupled receptor kinase 5 regulates thrombin signaling in platelets via PAR-1. Blood Adv. 6, 2319–2330 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Jones, C. I. et al. Mapping the platelet profile for functional genomic studies and demonstration of the effect size of the GP6 locus. J. Thromb. Haemost. 5, 1756–1765 (2007).

Article 
CAS 
PubMed 

Google Scholar
 

Rodriguez, B. A. T. et al. A platelet function modulator of thrombin activation is causally linked to cardiovascular disease and affects PAR4 receptor signaling. Am. J. Hum. Genet. 107, 211–221 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Li, C. et al. G protein-coupled receptor kinase 5 regulates thrombin signaling in platelets. Res. Pract. Thromb. Haemost. 8, 102556 (2024).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Heijnen, H. F., Oorschot, V., Sixma, J. J., Slot, J. W. & James, D. E. Thrombin stimulates glucose transport in human platelets via the translocation of the glucose transporter GLUT-3 from alpha-granules to the cell surface. J. Cell Biol. 138, 323–330 (1997).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Detwiler, T. C. & Zivkovic, R. V. Control of energy metabolism in platelets. A comparison of aerobic and anaerobic metabolism in washed rat platelets. Biochim. Biophys. Acta 197, 117–126 (1970).

Article 
CAS 
PubMed 

Google Scholar
 

Vanni, S. et al. Prognostic value of plasma lactate levels among patients with acute pulmonary embolism: the thrombo-embolism lactate outcome study. Ann. Emerg. Med. 61, 330–338 (2013).

Article 
PubMed 

Google Scholar
 

Vanni, S. et al. High plasma lactate levels are associated with increased risk of in-hospital mortality in patients with pulmonary embolism: high plasma lactate levels and PE. Acad. Emerg. Med. 18, 830–835 (2011).

Article 
PubMed 

Google Scholar
 

Leidi, A. et al. Risk stratification in patients with acute pulmonary embolism: current evidence and perspectives. J. Clin. Med. 11, 2533 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Hawkes, G. et al. Whole-genome sequencing analysis identifies rare, large-effect noncoding variants and regulatory regions associated with circulating protein levels. Nat. Genet. 57, 626–634 (2025).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Mann, G., Mora, S., Madu, G. & Adegoke, O. A. J. Branched-chain amino acids: catabolism in skeletal muscle and implications for muscle and whole-body metabolism. Front. Physiol. 12, 702826 (2021).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Cheng, J. et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science 381, eadg7492 (2023).

Article 
CAS 
PubMed 

Google Scholar
 

Spence, J. P. et al. Specificity, length and luck drive gene rankings in association studies. Nature 649, 918–925 (2026).

Article 
ADS 
CAS 
PubMed 

Google Scholar
 

Lotta, L. A. et al. Association between low-density lipoprotein cholesterol-lowering genetic variants and risk of type 2 diabetes: a meta-analysis. JAMA 316, 1383–1391 (2016).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Burgess, S. et al. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res. 4, 186 (2019).

Article 
PubMed 

Google Scholar
 

Gill, D. et al. Common pitfalls in drug target Mendelian randomization and how to avoid them. BMC Med. 22, 473 (2024).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Carugo, S., Sirtori, C. R., Corsini, A., Tokgozoglu, L. & Ruscica, M. PCSK9 inhibition and risk of diabetes: should we worry?. Curr. Atheroscler. Rep. 24, 995–1004 (2022).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Mahendran, Y. et al. Genetic evidence of a causal effect of insulin resistance on branched-chain amino acid levels. Diabetologia 60, 873–878 (2017).

Article 
CAS 
PubMed 

Google Scholar
 

Wang, Q., Holmes, M. V., Davey Smith, G. & Ala-Korpela, M. Genetic support for a causal role of insulin resistance on circulating branched-chain amino acids and inflammation. Diabetes Care 40, 1779–1786 (2017).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Filipski, K. J. et al. Discovery of first branched-chain ketoacid dehydrogenase kinase (BDK) inhibitor clinical candidate PF-07328948. J. Med. Chem. 68, 2466–2482 (2025).

Article 
CAS 
PubMed 

Google Scholar
 

Schlosser, P. et al. Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine. Nat. Genet. 55, 995–1008 (2023).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Surendran, P. et al. Rare and common genetic determinants of metabolic individuality and their effects on human health. Nat. Med. 1, 12 (2022).


Google Scholar
 

Reed, Z. E. et al. Exploring pleiotropy in Mendelian randomisation analyses: what are genetic variants associated with ‘cigarette smoking initiation’ really capturing? Genet. Epidemiol. 49, e22583 (2025).

Article 
CAS 
PubMed 

Google Scholar
 

Sollis, E. et al. The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource. Nucleic Acids Res. 51, D977–D985 (2023).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Kartau, J. & Pirinen, M. FINEMAP-miss: fine-mapping genome-wide association studies with missing genotype information. Bioinformatics 41, btaf616 (2025).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Yang, Z. et al. CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses. Nat. Genet. 55, 1057–1065 (2023).

Article 
CAS 
PubMed 

Google Scholar
 

Milani, L. et al. The Estonian Biobank’s journey from biobanking to personalized medicine. Nat. Commun. 16, 3270 (2025).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Leitsalu, L. et al. Cohort profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int. J. Epidemiol. 44, 1137–1147 (2015).

Article 
PubMed 

Google Scholar
 

Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Julkunen, H. et al. Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank. Nat. Commun. 14, 604 (2023).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Nightingale Health Biobank Collaborative Group Metabolomic and genomic prediction of common diseases in 700,217 participants in three national biobanks. Nat. Commun. 15, 10092 (2024).

Article 
ADS 
CAS 

Google Scholar
 

Ritchie, S. C. et al. Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants. Sci. Data 10, 64 (2023).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Mbatchou, J. et al. Computationally efficient whole-genome regression for quantitative and binary traits. Nat. Genet. 53, 1097–1103 (2021).

Article 
CAS 
PubMed 

Google Scholar
 

Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Kerimov, N. et al. A compendium of uniformly processed human gene expression and splicing quantitative trait loci. Nat. Genet. 53, 1290–1299 (2021).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).

Article 
PubMed 
PubMed Central 

Google Scholar
 

pyliftover. PyPI https://pypi.org/project/pyliftover/ (2024).

Shirley, M. D., Ma, Z., Pedersen, B. S. & Wheelan, S. J. Efficient ‘pythonic’ access to FASTA files using pyfaidx. Preprint at PeerJ https://doi.org/10.7287/peerj.preprints.970v1 (2015).

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. B 82, 1273–1300 (2020).

Article 
MathSciNet 

Google Scholar
 

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).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Benner, C. et al. Prospects of fine-mapping trait-associated genomic regions by using summary statistics from genome-wide association studies. Am. J. Hum. Genet. 101, 539–551 (2017).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Hormozdiari, F. et al. Colocalization of GWAS and eQTL signals detects target genes. Am. J. Hum. Genet. 99, 1245–1260 (2016).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

McLaren, W. et al. The Ensembl variant effect predictor. Genome Biol. 17, 122 (2016).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Skrivankova, V. W. et al. Strengthening the reporting of observational studies in epidemiology using mendelian randomisation (STROBE-MR): explanation and elaboration. BMJ 375, n2233 (2021).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Yavorska, O. O. & Burgess, S. MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data. Int. J. Epidemiol. 46, 1734–1739 (2017).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Tambets, R., Kolde, A., Kolberg, P., Love, M. I. & Alasoo, K. Extensive co-regulation of neighboring genes complicates the use of eQTLs in target gene prioritization. HGG Adv. 5, 100348 (2024).

CAS 
PubMed 
PubMed Central 

Google Scholar
 

Zhu, A. et al. MRLocus: Identifying causal genes mediating a trait through Bayesian estimation of allelic heterogeneity. PLoS Genet. 17, e1009455 (2021).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44, 512–525 (2015).

Article 
PubMed 
PubMed Central 

Google Scholar
 

van der Graaf, A. et al. MR-link-2: pleiotropy robust cis Mendelian randomization validated in three independent reference datasets of causality. Nat. Commun. 16, 6112 (2025).

Article 
ADS 
PubMed 
PubMed Central 

Google Scholar
 

Burgess, S., Zuber, V., Valdes-Marquez, E., Sun, B. B. & Hopewell, J. C. Mendelian randomization with fine-mapped genetic data: choosing from large numbers of correlated instrumental variables. Genet. Epidemiol. 41, 714–725 (2017).

Article 
PubMed 
PubMed Central 

Google Scholar
 

UK10K Consortium et al The UK10K project identifies rare variants in health and disease. Nature 526, 82–90 (2015).

Article 
ADS 

Google Scholar
 

Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Varadi, M. et al. AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences. Nucleic Acids Res. 52, D368–D375 (2024).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Meng, E. C. et al. UCSF ChimeraX: Tools for structure building and analysis. Protein Sci. 32, e4792 (2023).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar
 

Tambets, R. & Alasoo, K. Fine-mapping results for the EstBB-UKBB NMR metabolic trait meta-analysis. Zenodo https://doi.org/10.5281/zenodo.18132538 (2026).

Alasoo, K. & Jesse, M. Colocalisation results for the Tambets et al NMR metabolic trait GWAS study. Zenodo https://doi.org/10.5281/zenodo.17945143 (2025).