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Identifying genetic variants associated with circulating protein concentrations (protein quantitative trait loci; pQTLs) and integrating them with variants from genome-wide association studies (GWAS) may illuminate the proteome’s causal role in disease and bridge a knowledge gap regarding SNP-disease associations. We provide the results of GWAS of 71 high-value cardiovascular disease proteins in 6861 Framingham Heart Study participants and independent external replication. We report the mapping of over 16,000 pQTL variants and their functional relevance. We provide an integrated plasma protein-QTL database. Thirteen proteins harbor pQTL variants that match coronary disease-risk variants from GWAS or test causal for coronary disease by Mendelian randomization. Eight of these proteins predict new-onset cardiovascular disease events in Framingham participants. We demonstrate that identifying pQTLs, integrating them with GWAS results, employing Mendelian randomization, and prospectively testing protein-trait associations holds potential for elucidating causal genes, proteins, and pathways for cardiovascular disease and may identify targets for its prevention and treatment. Genetic variation can influence levels of disease-related plasma proteins and, thus, contribute to the pathogenesis of complex diseases. Here, the authors perform genome-wide QTL analysis for 71 plasma proteins to identify causal proteins for coronary heart disease and provide a molecular QTL browser.

Identifying methylation quantitative trait loci (meQTLs) and integrating them with disease-associated variants from genome-wide association studies (GWAS) may illuminate functional mechanisms underlying genetic variant-disease associations. Here, we perform GWAS of >415 thousand CpG methylation sites in whole blood from 4170 individuals and map 4.7 million cis- and 630 thousand trans- meQTL variants targeting >120 thousand CpGs. Independent replication is performed in 1347 participants from two studies. By linking cis- meQTL variants with GWAS results for cardiovascular disease (CVD) traits, we identify 92 putatively causal CpGs for CVD traits by Mendelian randomization analysis. Further integrating gene expression data reveals evidence of cis CpG-transcript pairs causally linked to CVD. In addition, we identify 22 trans- meQTL hotspots each targeting more than 30 CpGs and find that trans- meQTL hotspots appear to act in cis on expression of nearby transcriptional regulatory genes. Our findings provide a powerful meQTL resource and shed light on DNA methylation involvement in human diseases. Differentially methylated CpGs can inform on disease mechanisms and be useful as biomarkers. Here, the authors perform GWAS for DNA methylation in whole blood, cis - and trans -meQTL mapping, followed by Mendelian randomization analysis that links meQTLs with cardiovascular diseases.

Type 2 diabetes is characterized by insulin resistance and a gradual loss of pancreatic beta cell mass and function1,2. Currently, there are no therapies proven to prevent beta cell loss and some, namely insulin secretagogues, have been linked to accelerated beta cell failure, thereby limiting their use in type 2 diabetes3,4. The adipokine adipsin/complement factor D controls the alternative complement pathway and generation of complement component C3a, which acts to augment beta cell insulin secretion5. In contrast to other insulin secretagogues, we show that chronic replenishment of adipsin in diabetic db/db mice ameliorates hyperglycemia and increases insulin levels while preserving beta cells by blocking dedifferentiation and death. Mechanistically, we find that adipsin/C3a decreases the phosphatase Dusp26; forced expression of Dusp26 in beta cells decreases expression of core beta cell identity genes and sensitizes to cell death. In contrast, pharmacological inhibition of DUSP26 improves hyperglycemia in diabetic mice and protects human islet cells from cell death. Pertaining to human health, we show that higher concentrations of circulating adipsin are associated with a significantly lower risk of developing future diabetes among middle-aged adults after adjusting for body mass index (BMI). Collectively, these data suggest that adipsin/C3a and DUSP26-directed therapies may represent a novel approach to achieve beta cell health to treat and prevent type 2 diabetes.

Chronic kidney disease (CKD) is defined by reduced estimated glomerular filtration rate (eGFR). Previous genetic studies have implicated regulatory mechanisms contributing to CKD. Here we present epigenome-wide association studies of eGFR and CKD using whole-blood DNA methylation of 2264 ARIC Study and 2595 Framingham Heart Study participants to identify epigenetic signatures of kidney function. Of 19 CpG sites significantly associated ( P  < 1e-07) with eGFR/CKD and replicated, five also associate with renal fibrosis in biopsies from CKD patients and show concordant DNA methylation changes in kidney cortex. Lead CpGs at PTPN6 / PHB2 , ANKRD11 , and TNRC18 map to active enhancers in kidney cortex. At PTPN6 / PHB2 cg19942083, methylation in kidney cortex associates with lower renal PTPN6 expression, higher eGFR, and less renal fibrosis. The regions containing the 243 eGFR-associated ( P  < 1e-05) CpGs are significantly enriched for transcription factor binding sites of EBF1, EP300, and CEBPB ( P  < 5e-6). Our findings highlight kidney function associated epigenetic variation. Genome-wide association studies of kidney function show enrichment of associated genetic variants in regulatory regions. Here, the authors perform epigenome-wide association studies of kidney function and disease, identifying 19 CpG sites significantly associated with these.

DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome‐wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow‐up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry‐stratified meta‐analysis of all‐cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10−7, of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm‐based prediction models for all‐cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C‐index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, PMR = 4.1 × 10−4) and negatively associated with longevity (Beta = −1.9, PMR = 0.02). Pathway analysis revealed that genes associated with mortality‐related CpGs are enriched for immune‐ and cancer‐related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk. DNA methylation (DNAm) is an important epigenetic regulatory mechanism and is associated with many diseases and with human aging. Our study demonstrated that inter‐individual variation in DNAm is associated with all‐cause mortality risk and with cause‐specific mortality. We built a prediction model by integrating DNAm with clinical risk factors and we show that doing so can improve mortality prediction.

Biomarkers common to chronic kidney disease (CKD) and cardiovascular disease (CVD) may reflect early impairments underlying both diseases. We evaluated associations of 71 CVD-related plasma proteins measured in 2,873 Framingham Heart Study (FHS) Offspring cohort participants with cross-sectional continuous eGFR and with longitudinal change in eGFR from baseline to follow-up (ΔeGFR). We also evaluated the associations of the 71 CVD proteins with the following dichotomous secondary outcomes: prevalent CKD stage ≥3 (cross-sectional), new-onset CKD stage ≥3 (longitudinal), and rapid decline in eGFR (longitudinal). Proteins significantly associated with eGFR and ΔeGFR were subsequently validated in 3,951 FHS Third Generation cohort participants and were tested using Mendelian randomization (MR) analysis to infer putatively causal relations between plasma protein biomarkers and kidney function. In cross-sectional analysis, 37 protein biomarkers were significantly associated with eGFR at FDR<0.05 in the FHS Offspring cohort and 20 of these validated in the FHS Third Generation cohort at p<0.05/37. In longitudinal analysis, 27 protein biomarkers were significantly associated with ΔeGFR at FDR<0.05 and 12 of these were validated in the FHS Third Generation cohort at p<0.05/27. Additionally, 35 protein biomarkers were significantly associated with prevalent CKD, five were significantly associated with new-onset CKD, and 17 were significantly associated with rapid decline in eGFR. MR suggested putatively causal relations of melanoma cell adhesion molecule (MCAM; -0.011±0.003 mL/min/1.73m2, p = 5.11E-5) and epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1; -0.006±0.002 mL/min/1.73m2, p = 0.0001) concentration with eGFR. Eight protein biomarkers were consistently associated with eGFR in cross-sectional and longitudinal analysis in both cohorts and may capture early kidney impairment; others were implicated in association and causal inference analyses. A subset of CVD protein biomarkers may contribute causally to the pathogenesis of kidney impairment and should be studied as targets for CKD treatment and early prevention.

Background Substantial efforts have been dedicated to exploring the link between genetic regulation and the proteome, informing studies of complex trait mechanisms. Most of these efforts have been limited to populations of European ancestry. Results We conduct an Olink protein quantitative trait locus (pQTL) analysis on 1245 proteins involving 1033 self-identified African American (AA) and 1764 non-Hispanic White (NHW) participants from the Women’s Health Initiative and Framingham Heart Study. For replication of candidate pQTLs, we use data from 534 self-identified AA adults from the Jackson Heart Study and protein genome-wide association analysis statistics from the UK Biobank Pharma Proteomics Project, including 54,219 participants, of whom 931 are of African ancestry. In total, we identify and validate 5103 pQTLs (4496 or 88% cis- and 602 or 12% trans-pQTLs) for 983 proteins. Among these, 195 are previously unreported, with most (166 or 85%) identified in our AA sample, many of which were essentially monomorphic in European reference populations. Several of these newly identified African ancestry-specific pQTLs have been reported in ClinVar; our results suggest impact on circulating protein levels, potentially bolstering evidence for clinical significance. We identify a “cis pQTL hotspot” within the leukocyte receptor gene cluster on human chromosome 19q13.4. We also provide examples where a particular cis-pQTL, identified through conditional analysis, offers biological insights into an overlapping GWAS signal for disease susceptibility. Conclusions The identification of previously undescribed African ancestry-specific pQTLs contributes to understanding protein genetic regulation and highlights the significance of proteomic analysis in diverse populations.

Hyperuricaemia, a highly heritable trait, is a key risk factor for gout. We aimed to identify novel genes associated with serum uric acid concentration and gout. Genome-wide association studies were done for serum uric acid in 7699 participants in the Framingham cohort and in 4148 participants in the Rotterdam cohort. Genome-wide significant single nucleotide polymorphisms (SNPs) were replicated in white (n=11 024) and black (n=3843) individuals who took part in the study of Atherosclerosis Risk in Communities (ARIC). The SNPs that reached genome-wide significant association with uric acid in either the Framingham cohort (p<5·0×10 −8) or the Rotterdam cohort (p<1·0×10 −7) were evaluated with gout. The results obtained in white participants were combined using meta-analysis. Three loci in the Framingham cohort and two in the Rotterdam cohort showed genome-wide association with uric acid. Top SNPs in each locus were: missense rs16890979 in SLC2A9 (p=7·0×10 −168 and 2·9×10 −18 for white and black participants, respectively); missense rs2231142 in ABCG2 (p=2·5×10 −60 and 9·8×10 −4), and rs1165205 in SLC17A3 (p=3·3×10 −26 and 0·33). All SNPs were direction-consistent with gout in white participants: rs16890979 (OR 0·59 per T allele, 95% CI 0·52–0·68, p=7·0×10 −14), rs2231142 (1·74, 1·51–1·99, p=3·3×10 −15), and rs1165205 (0·85, 0·77–0·94, p=0·002). In black participants of the ARIC study, rs2231142 was direction-consistent with gout (1·71, 1·06–2·77, p=0·028). An additive genetic risk score of high-risk alleles at the three loci showed graded associations with uric acid (272–351 μmol/L in the Framingham cohort, 269–386 μmol/L in the Rotterdam cohort, and 303–426 μmol/L in white participants of the ARIC study) and gout (frequency 2–13% in the Framingham cohort, 2–8% in the Rotterdam cohort, and 1–18% in white participants in the ARIC study). We identified three genetic loci associated with uric acid concentration and gout. A score based on genes with a putative role in renal urate handling showed a substantial risk for gout. Netherlands Organisation for Scientific Research (NWO); the National Heart, Lung, and Blood Institute.

Leukocyte telomere length (LTL) is a trait associated with risk of cardiovascular disease and cancer, the 2 major disease categories that largely define longevity in the United States. However, it remains unclear whether LTL is associated with the human life span. To examine whether LTL is associated with the life span of contemporary humans. This cohort study included 3259 adults of European ancestry from the Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), and Women's Health Initiative (WHI). Leukocyte telomere length was measured in 1992 and 1997 in the CHS, from 1995 to 1998 in the FHS, and from 1993 to 1998 in the WHI. Data analysis was conducted from February 2017 to December 2019. Death and LTL, measured by Southern blots of the terminal restriction fragments, were the main outcomes. Cause of death was adjudicated by end point committees. The analyzed sample included 3259 participants (2342 [71.9%] women), with a median (range) age of 69.0 (50.0-98.0) years at blood collection. The median (range) follow-up until death was 10.9 (0.2-23.0) years in CHS, 19.7 (3.4-23.0) years in FHS, and 16.6 (0.5-20.0) years in WHI. During follow-up, there were 1525 deaths (482 [31.6%] of cardiovascular disease; 373 [24.5%] of cancer, and 670 [43.9%] of other or unknown causes). Short LTL, expressed in residual LTL, was associated with increased mortality risk. Overall, the hazard ratio for all-cause mortality for a 1-kilobase decrease in LTL was 1.34 (95% CI, 1.21-1.47). This association was stronger for noncancer causes of death (cardiovascular death: hazard ratio, 1.28; 95% CI, 1.08-1.52; cancer: hazard ratio, 1.13; 95% CI, 0.93-1.36; and other causes: hazard ratio, 1.53; 95% CI, 1.32-1.77). The results of this study indicate that LTL is associated with a natural life span limit in contemporary humans.

Growth differentiation factor-15 (GDF-15), soluble ST2 (sST2), and high-sensitivity troponin I (hsTnI) are emerging predictors of adverse clinical outcomes. We examined whether circulating concentrations are related to the development of kidney disease in the community. Plasma GDF-15, sST2, and hsTnI concentrations were measured in 2614 Framingham Offspring cohort participants (mean age 57 years, 54% women) at the sixth examination cycle (1995-1998). Associations of biomarkers with incident chronic kidney disease [CKD, eGFR <60 mL · min(-1) · (1.73 m(2)) (-1), n = 276], microalbuminuria (urinary albumin to creatinine ratio ≥25 mg/g in women and 17 mg/g in men, n = 191), and rapid decline in renal function [decline in eGFR ≥3 mL · min(-1) · (1.73 m(2)) (-1) per year, n = 237], were evaluated using multivariable logistic regression; P < 0.006 was considered statistically significant in primary analyses. Participants were followed over a mean of 9.5 years. Higher plasma GDF-15 was associated with incident CKD [multivariable-adjusted odds ratio (OR) 1.9 per 1-U increase in log-GDF-15, 95% CI 1.6-2.3, P < 0.0001] and rapid decline in renal function (OR, 1.6; 95% CI, 1.3-1.8; P < 0.0001). GDF-15, sST2, and hsTnI had suggestive associations with incident microalbuminuria but did not meet the prespecified P-value threshold after multivariable adjustment. Adding plasma GDF-15 to clinical covariates improved risk prediction of incident CKD: the c-statistic increased from 0.826 to 0.845 (P = 0.0007), and categorical net reclassification was 6.3% (95% CI, 2.7-9.9%). Higher circulating GDF-15 is associated with incident renal outcomes and improves risk prediction of incident CKD. These findings may provide insights into the mechanisms of renal injury.