Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes.

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.

Plasma Proteomics to Identify Drug Targets for Ischemic Heart Disease.

BACKGROUND: 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. OBJECTIVES: The purpose of this study was to examine associations of proteomics and genetics data with IHD in population studies to discover novel preventive treatments. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.

Conventional and genetic associations of adiposity with 1463 proteins in relatively lean Chinese adults.

Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m2, with only 6% being obese (i.e. BMI ≥ 30 kg/m2). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m2). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using cis-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.

Pleiotropic genetic architecture and novel loci for C-reactive protein levels.

C-reactive protein is involved in a plethora of pathophysiological conditions. Many genetic loci associated with C-reactive protein are annotated to lipid and glucose metabolism genes supporting common biological pathways between inflammation and metabolic traits. To identify novel pleiotropic loci, we perform multi-trait analysis of genome-wide association studies on C-reactive protein levels along with cardiometabolic traits, followed by a series of in silico analyses including colocalization, phenome-wide association studies and Mendelian randomization. We find 41 novel loci and 19 gene sets associated with C-reactive protein with various pleiotropic effects. Additionally, 41 variants colocalize between C-reactive protein and cardiometabolic risk factors and 12 of them display unexpected discordant effects between the shared traits which are translated into discordant associations with clinical outcomes in subsequent phenome-wide association studies. Our findings provide insights into shared mechanisms underlying inflammation and lipid metabolism, representing potential preventive and therapeutic targets.

Genetic analysis of over half a million people characterises C-reactive protein loci.

Chronic low-grade inflammation is linked to a multitude of chronic diseases. We report the largest genome-wide association study (GWAS) on C-reactive protein (CRP), a marker of systemic inflammation, in UK Biobank participants (N = 427,367, European descent) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (total N = 575,531 European descent). We identify 266 independent loci, of which 211 are not previously reported. Gene-set analysis highlighted 42 gene sets associated with CRP levels (p ≤ 3.2 ×10-6) and tissue expression analysis indicated a strong association of CRP related genes with liver and whole blood gene expression. Phenome-wide association study identified 27 clinical outcomes associated with genetically determined CRP and subsequent Mendelian randomisation analyses supported a causal association with schizophrenia, chronic airway obstruction and prostate cancer. Our findings identified genetic loci and functional properties of chronic low-grade inflammation and provided evidence for causal associations with a range of diseases.

Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes.

Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.