Wagner R, Heni M, Tabák AG et al (2021) Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes. Nat Med 27(1):49–57. https://doi.org/10.1038/s41591-020-1116-9
Article CAS PubMed Google Scholar
Guariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE (2014) Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract 103(2):137–149. https://doi.org/10.1016/j.diabres.2013.11.002
Article CAS PubMed Google Scholar
Wu L, Shi W, Long J et al (2018) A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer. Nat Genet 50(7):968–978. https://doi.org/10.1038/s41588-018-0132-x
Article CAS PubMed PubMed Central Google Scholar
Wu L, Wang J, Cai Q et al (2019) Identification of novel susceptibility loci and genes for prostate cancer risk: a transcriptome-wide association study in over 140,000 European descendants. Cancer Res 79(13):3192–3204. https://doi.org/10.1158/0008-5472.CAN-18-3536
Article CAS PubMed PubMed Central Google Scholar
Zhu J, Yang Y, Kisiel JB et al (2021) Integrating genome and methylome data to identify candidate DNA methylation biomarkers for pancreatic cancer risk. Cancer Epidemiol Prev Biomark 30(11):2079–2087. https://doi.org/10.1158/1055-9965.EPI-21-0400
Wu L, Shu X, Bao J et al (2019) Analysis of over 140,000 European descendants identifies genetically predicted blood protein biomarkers associated with prostate cancer risk. Cancer Res 79(18):4592–4598. https://doi.org/10.1158/0008-5472.CAN-18-3997
Article CAS PubMed PubMed Central Google Scholar
Sun Y, Zhu J, Zhou D et al (2021) A transcriptome-wide association study of Alzheimer’s disease using prediction models of relevant tissues identifies novel candidate susceptibility genes. Genome Med 13(1):1–11. https://doi.org/10.1186/s13073-021-00959-y
Sun Y, Zhou D, Rahman MR et al (2022) A transcriptome-wide association study identifies novel blood-based gene biomarker candidates for Alzheimer’s disease risk. Hum Mol Genet 31(2):289–299. https://doi.org/10.1093/hmg/ddab229
Wu C, Zhu J, King A et al (2021) Novel strategy for disease risk prediction incorporating predicted gene expression and DNA methylation data: a multi-phased study of prostate cancer. Cancer Commun 41(12):1387–1397. https://doi.org/10.1002/cac2.12205
Voight BF, Scott LJ, Steinthorsdottir V et al (2010) Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet 42(7):579–589. https://doi.org/10.1038/ng.609
Article CAS PubMed PubMed Central Google Scholar
Morris AP, Voight BF, Teslovich TM et al (2012) Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet 44(9):981–990. https://doi.org/10.1038/ng.2383
Article CAS PubMed PubMed Central Google Scholar
Mahajan A, Taliun D, Thurner M et al (2018) Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat Genet 50(11):1505–1513. https://doi.org/10.1038/s41588-018-0241-6
Article CAS PubMed PubMed Central Google Scholar
Scott RA, Scott LJ, Mägi R et al (2017) An expanded genome-wide association study of type 2 diabetes in Europeans. Diabetes 66(11):2888–2902. https://doi.org/10.2337/db16-1253
Article CAS PubMed PubMed Central Google Scholar
Chen J, Sun M, Adeyemo A et al (2019) Genome-wide association study of type 2 diabetes in Africa. Diabetologia 62(7):1204–1211. https://doi.org/10.1007/s00125-019-4880-7
Article PubMed PubMed Central Google Scholar
Adeyemo AA, Zaghloul NA, Chen G et al (2019) ZRANB3 is an African-specific type 2 diabetes locus associated with beta-cell mass and insulin response. Nat Commun 10(1):3195. https://doi.org/10.1038/s41467-019-10967-7
Article CAS PubMed PubMed Central Google Scholar
Spracklen CN, Horikoshi M, Kim YJ et al (2020) Identification of type 2 diabetes loci in 433,540 East Asian individuals. Nature 582(7811):240–245. https://doi.org/10.1038/s41586-020-2263-3
Article CAS PubMed PubMed Central Google Scholar
Suzuki K, Akiyama M, Ishigaki K et al (2019) Identification of 28 new susceptibility loci for type 2 diabetes in the Japanese population. Nat Genet 51(3):379–386. https://doi.org/10.1038/s41588-018-0332-4
Article CAS PubMed Google Scholar
Qi Q, Stilp AM, Sofer T et al (2017) Genetics of type 2 diabetes in U.S. Hispanic/Latino individuals: results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Diabetes 66(5):1419–1425. https://doi.org/10.2337/db16-1150
Article CAS PubMed PubMed Central Google Scholar
Huerta A, Cole JB, Dornbos P et al (2021) 245-OR: comprehensive Genome-Wide Association Study (GWAS) meta-analysis using TOPMed imputation in Latinos identifies rare variation associated with type 2 diabetes (T2D). Diabetes 70(Supplement_1):245-OR. https://doi.org/10.2337/db21-245-OR
Rodríguez JE, Campbell KM (2017) Racial and ethnic disparities in prevalence and care of patients with type 2 diabetes. Clin Diabetes 35(1):66–70. https://doi.org/10.2337/cd15-0048
Article PubMed PubMed Central Google Scholar
Huth C, von Toerne C, Schederecker F et al (2019) Protein markers and risk of type 2 diabetes and prediabetes: a targeted proteomics approach in the KORA F4/FF4 study. Eur J Epidemiol 34(4):409–422. https://doi.org/10.1007/s10654-018-0475-8
Article CAS PubMed Google Scholar
Ngo D, Benson MD, Long JZ et al (2021) Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk. JCI Insight 6(5):1–18
Zhu J, O’Mara TA, Liu D et al (2021) Associations between genetically predicted circulating protein concentrations and endometrial cancer risk. Cancers (Basel) 13(9):2088. https://doi.org/10.3390/cancers13092088
Article CAS PubMed PubMed Central Google Scholar
Zhang J, Dutta D, Köttgen A et al (2022) Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies. Nat Genet 54(5):593–602. https://doi.org/10.1038/s41588-022-01051-w
Article CAS PubMed PubMed Central Google Scholar
Wingo AP, Liu Y, Gerasimov ES et al (2021) Integrating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer’s disease pathogenesis. Nat Genet 53(2):143–146. https://doi.org/10.1038/s41588-020-00773-z
Article CAS PubMed PubMed Central Google Scholar
Wingo TS, Gerasimov ES, Liu Y et al (2022) Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder. Mol Psychiatry 27(7):3075–3084. https://doi.org/10.1038/s41380-022-01544-4
Article CAS PubMed PubMed Central Google Scholar
Sun BB, Maranville JC, Peters JE et al (2018) Genomic atlas of the human plasma proteome. Nature 558(7708):73–79. https://doi.org/10.1038/s41586-018-0175-2
Comments (0)