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OBJECTIVE: Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis -protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D. RESULTS: Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73–0.82) to 0.88 (0.85–0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D. CONCLUSIONS: Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D. [ABSTRACT FROM AUTHOR]

Integrated analyses of plasma proteomic and genetic markers in prospective studies can clarify the causal relevance of proteins and discover novel targets for ischemic heart disease (IHD) and other diseases. The purpose of this study was to examine associations of proteomics and genetics data with IHD in population studies to discover novel preventive treatments. We conducted a nested case-cohort study in the China Kadoorie Biobank (CKB) involving 1,971 incident IHD cases and 2,001 subcohort participants who were genotyped and free of prior cardiovascular disease. We measured 1,463 proteins in the stored baseline samples using the OLINK EXPLORE panel. Cox regression yielded adjusted HRs for IHD associated with individual proteins after accounting for multiple testing. Moreover, cis -protein quantitative loci (pQTLs) identified for proteins in genome-wide association studies of CKB and of UK Biobank were used as instrumental variables in separate 2-sample Mendelian randomization (MR) studies involving global CARDIOGRAM+C4D consortium (210,842 IHD cases and 1,378,170 controls). Overall 361 proteins were significantly associated at false discovery rate <0.05 with risk of IHD (349 positively, 12 inversely) in CKB, including N-terminal prohormone of brain natriuretic peptide and proprotein convertase subtilisin/kexin type 9. Of these 361 proteins, 212 had cis -pQTLs in CKB, and MR analyses of 198 variants in CARDIOGRAM+C4D identified 13 proteins that showed potentially causal associations with IHD. Independent MR analyses of 307 cis -pQTLs identified in Europeans replicated associations for 4 proteins (FURIN, proteinase-activated receptor-1, Asialoglycoprotein receptor-1, and matrix metalloproteinase-3). Further downstream analyses showed that FURIN, which is highly expressed in endothelial cells, is a potential novel target and matrix metalloproteinase-3 a potential repurposing target for IHD. Integrated analyses of proteomic and genetic data in Chinese and European adults provided causal support for FURIN and multiple other proteins as potential novel drug targets for treatment of IHD. [Display omitted] [ABSTRACT FROM AUTHOR]

Some observational studies indicate a link between blood lead and kidney function although results remain controversial. In this study, Mendelian randomisation (MR) analysis was applied to obtain unconfounded estimates of the casual association of genetically determined blood lead with estimated glomerular filtration rate (eGFR) and the risk of chronic kidney disease (CKD). Data from the largest genome-wide association studies (GWAS) on blood lead, eGFR and CKD, from predominantly ethnically European populations, were analysed in total, as well as separately in individuals with or without type 2 diabetes mellitus. Inverse variance weighted (IVW) method, weighted median (WM)-based method, MR-Egger, MR-Pleiotropy RESidual Sum and Outlier (PRESSO) as well as the leave-one-out method were applied. In a general population, lifetime blood lead levels had no significant effect on risk of CKD (IVW: p = 0.652) and eGFR (IVW: p = 0.668). After grouping by type 2 diabetes status (no diabetes vs. diabetes), genetically higher levels of blood lead had a significant negative impact among subjects with type 2 diabetes (IVW = Beta: −0.03416, p = 0.0132) but not in subjects without (IVW: p = 0.823), with low likelihood of heterogeneity for any estimates (IVW p > 0.158). MR-PRESSO did not highlight any outliers. Pleiotropy test, with very negligible intercept and insignificant p-value, indicated a low likelihood of pleiotropy for all estimations. The leave-one-out method demonstrated that links were not driven by a single SNP. Our results show, for the first time, that among subjects with type 2 diabetes, higher blood lead levels are potentially related to less favourable renal function. Further studies are needed to confirm our results. Key messages: What is already known about this subject? Chronic kidney disease is associated with unfavourable lifestyle behaviours and conditions such as type 2 diabetes. Observational studies have reported an association between blood lead and reduced estimated glomerular filtration rate, but the relationship between lead exposure and renal function remains controversial. What is the key question? Using Mendelian randomisation with data from 5433 individuals from the UK and Australian populations, does genetically determined blood lead have a potentially causal effect on estimated glomerular filtration rate and the risk of chronic kidney disease? What are the new findings? Blood lead levels have a potentially causal effect on reduced renal function in individuals with type 2 diabetes. In subjects without diabetes, no such causal relationship was identified. How might this impact on clinical practice in the foreseeable future? This highlights the risk of elevated blood lead, for example, due to environmental exposure, amongst those with type 2 diabetes, which may predispose them to impaired renal function. [ABSTRACT FROM AUTHOR]