Glucagon-like peptide 1 receptor agonist use and risk of thyroid cancer: Scandinavian cohort study.

OBJECTIVE: To investigate whether use of glucagon-like peptide 1 (GLP1) receptor agonists is associated with increased risk of thyroid cancer. DESIGN: Scandinavian cohort study. SETTING: Denmark, Norway, and Sweden, 2007-21. PARTICIPANTS: Patients who started GLP1 receptor agonist treatment were compared with patients who started dipeptidyl peptidase 4 (DPP4) inhibitor treatment, and in an additional analysis, patients who started sodium-glucose cotransporter 2 (SGLT2) inhibitor treatment. MAIN OUTCOME MEASURES: Thyroid cancer identified from nationwide cancer registers. An active-comparator new user study design was used to minimise risks of confounding and time related biases from using real world studies of drug effects. Cox regression was used to estimate hazard ratios, controlling for potential confounders with propensity score weighting. RESULTS: The mean follow-up time was 3.9 years (standard deviation 3.5 years) in the GLP1 receptor agonist group and 5.4 years (standard deviation 3.5 years) in the DPP4 inhibitor group. 76 of 145 410 patients (incidence rate 1.33 events per 10 000 person years) treated with GLP1 receptor agonists and 184 of 291 667 patients (incidence rate 1.46 events per 10 000 person years) treated with DPP4 inhibitors developed thyroid cancer. GLP1 receptor agonist use was not associated with increased risk of thyroid cancer (hazard ratio 0.93, 95% confidence interval 0.66 to 1.31; rate difference -0.13, 95% confidence interval -0.61 to 0.36 events per 10 000 person years). The hazard ratio for medullary thyroid cancer was 1.19 (0.37 to 3.86). In the additional analysis comparing the GLP1 receptor agonist group with the SGLT2 inhibitor group, the hazard ratio for thyroid cancer was 1.16 (0.65 to 2.05). CONCLUSIONS: In this large cohort study using nationwide data from three countries, GLP1 receptor agonist use was not associated with a substantially increased risk of thyroid cancer over a mean follow-up of 3.9 years. In the main analysis comparing GLP1 receptor agonists with DPP4 inhibitors, the upper limit of the confidence interval was consistent with no more than a 31% increase in relative risk.

Association of inflammatory markers with incident heart failure or cancer in the HUNT3 and Health ABC population studies.

AIMS: To investigate the relationship between chronic low-grade inflammation, as measured by high-sensitivity C-reactive protein (hsCRP) levels, and incident heart failure (HF) or cancer. METHODS: We assessed the relationship between baseline hsCRP concentrations and subsequent HF or cancer in two community-based cohorts, the Trøndelag Health Study (HUNT3) and the Health, Aging and Body Composition (ABC) study. In the latter, the analysis was replicated with interleukin (IL)-1, IL-6, or tumour necrosis factor (TNF)-α instead of hsCRP. RESULTS: In HUNT3, hsCRP was measured in 47,163 subjects (mean age 52.3 ± 15.8 years). During a median follow-up of 12.1 years, 2,034 (4.3%) individuals developed HF and 5,024 (10.7%) cancer, with 442 (0.9%) being diagnosed with both. After adjusting for age, male sex, diabetes, obesity, previous or current smoking, and comorbidities, elevated baseline hsCRP was associated with a higher risk of HF or cancer (HR 1.09; 95%CI, 1.07-1.10). In the Health ABC study, hsCRP levels were assessed in 2,803 participants, who had a mean age of 72.6 ± 2.9 years and a higher burden of comorbidities than in HUNT3. During a median follow-up of 8.2 years, HF and cancer were diagnosed in 346 (12.3%) and 776 (27.7%) subjects, respectively, with 77 (2.7%) having both conditions. After adjusting for the same variables used for the HUNT3 cohort, hsCRP remained significantly associated with incident HF or cancer (HR 1.11; 95%CI, 1.05-1.18), as were IL-1 (HR 1.15; 1.07-1.24), IL-6 (HR 1.09; 1.02-1.17), and TNF-α (HR 1.15; 1.07-1.24). CONCLUSIONS: A state of chronic, low-grade inflammation captured by an increase in hsCRP levels is associated with an increased risk of developing HF or cancer, with potential implications for clinical trials with anti-inflammatory therapies.

There is an increasing recognition that cardiovascular (CV) risk factors portend an increased risk of both heart failure (HF) and cancer. Chronic, low-grade inflammation might represent a shared pathogenic pathway underlying the association between these risk factors, HF, and malignancy. The biomarker high-sensitivity C-reactive protein (hsCRP) might add prognostic information on CV and cancer risk by capturing this inflammatory state. In this study we analysed the association of inflammation, as assessed by baseline measurement of hsCRP, and the risk of developing HF and cancer in two community-based prospective studies, the Trøndelag Health Study (HUNT3) and the Health, Aging and Body Composition (Health ABC) study.In these cohorts, comprising more than 50,000 individuals, inflammation at baseline was associated with an increased risk of incident HF or cancer during a median follow-up of 8-12 years, after adjusting for traditional risk factors and comorbidities.In the Health ABC study sample, three inflammatory markers other than hsCRP, namely interleukin (IL)-1, IL-6, or tumour necrosis factor α, performed similarly to hsCRP in predicting the risk of incident HF or cancer. These results provide insights into the interconnection between HF and cancer and reinforce the concept that low-grade, chronic inflammation promotes the development of both HF and cancer and, thereby, might be targeted for prevention of either condition. Furthermore, our findings confirm the reliability of hsCRP as a biomarker to select individuals who may benefit from anti-inflammatory treatments to reduce CV and cancer events.

Association of glucagon-like peptide-1 receptor agonists with serious liver events among patients with type 2 diabetes: A Scandinavian cohort study.

BACKGROUND AND AIMS: Clinical trials suggest that glucagon-like peptide-1 (GLP-1) receptor agonists may have beneficial effects on NAFLD, but the impact on hard hepatic end points is unknown. We assessed the association between the use of GLP-1 receptor agonists and the risk of serious liver events in routine clinical practice. APPROACH AND RESULTS: Cohort study using data from nationwide registers in Sweden, Denmark, and Norway, 2007-2020, including 91,479 initiators of GLP-1 receptor agonists and 244,004 initiators of the active comparator, dipeptidyl peptidase-4 inhibitors, without a history of chronic liver disease other than NAFLD/NASH. The primary outcome was serious liver events: a composite of incident compensated and decompensated cirrhosis and HCC. Secondary outcomes were the individual components of the primary outcome. Cox regression was used to estimate HRs, using propensity score weighting to control for confounding. Users of GLP-1 receptor agonists had 608 serious liver events (adjusted incidence rate: 16.9 events per 10,000 person-years), compared with 1770 events among users of dipeptidyl peptidase-4 inhibitors (19.2 events per 10,000 person-years). The adjusted HR was 0.85 (95% CI: 0.75 to 0.97), and the rate difference was -2.1 (-4.4 to 0.1) events per 10,000 person-years. In secondary outcome analyses, the adjusted HR was 0.85 (0.75 to 0.97) for compensated and decompensated cirrhosis and 1.05 (0.80 to 1.39) for HCC. CONCLUSIONS: The use of GLP-1 receptor agonists was associated with a significantly reduced risk of serious liver events, driven by a reduction of compensated and decompensated cirrhosis.

A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk.

A reliable, individualized, and dynamic surrogate of cardiovascular risk, synoptic for key biologic mechanisms, could shorten the path for drug development, enhance drug cost-effectiveness and improve patient outcomes. We used highly multiplexed proteomics to address these objectives, measuring about 5000 proteins in each of 32,130 archived plasma samples from 22,849 participants in nine clinical studies. We used machine learning to derive a 27-protein model predicting 4-year likelihood of myocardial infarction, stroke, heart failure, or death. The 27 proteins encompassed 10 biologic systems, and 12 were associated with relevant causal genetic traits. We independently validated results in 11,609 participants. Compared to a clinical model, the ratio of observed events in quintile 5 to quintile 1 was 6.7 for proteins versus 2.9 for the clinical model, AUCs (95% CI) were 0.73 (0.72 to 0.74) versus 0.64 (0.62 to 0.65), c-statistics were 0.71 (0.69 to 0.72) versus 0.62 (0.60 to 0.63), and the net reclassification index was +0.43. Adding the clinical model to the proteins only improved discrimination metrics by 0.01 to 0.02. Event rates in four predefined protein risk categories were 5.6, 11.2, 20.0, and 43.4% within 4 years; median time to event was 1.71 years. Protein predictions were directionally concordant with changed outcomes. Adverse risks were predicted for aging, approaching an event, anthracycline chemotherapy, diabetes, smoking, rheumatoid arthritis, cancer history, cardiovascular disease, high systolic blood pressure, and lipids. Reduced risks were predicted for weight loss and exenatide. The 27-protein model has potential as a "universal" surrogate end point for cardiovascular risk.

Use of incretin-based drugs and risk of cholangiocarcinoma: Scandinavian cohort study.

AIMS/HYPOTHESIS: Concerns have been raised regarding a potential association of use of the incretin-based drugs dipeptidyl peptidase 4 (DPP4) inhibitors and glucagon-like peptide-1 (GLP-1)-receptor agonists with risk of cholangiocarcinoma. We examined this association in nationwide data from three countries. METHODS: We used data from nationwide registers in Sweden, Denmark and Norway, 2007-2018, to conduct two cohort studies, one for DPP4 inhibitors and one for GLP-1-receptor agonists, to investigate the risk of incident cholangiocarcinoma compared with an active-comparator drug class (sulfonylureas). The cohorts included patients initiating treatment episodes with DPP4 inhibitors vs sulfonylureas, and GLP-1-receptor agonists vs sulfonylureas. We used Cox regression models, adjusted for potential confounders, to estimate hazard ratios from day 366 after treatment initiation to account for cancer latency. RESULTS: The main analyses of DPP4 inhibitors included 1,414,144 person-years of follow-up from 222,577 patients receiving DPP4 inhibitors (median [IQR] follow-up time, 4.5 [2.6-7.0] years) and 123,908 patients receiving sulfonylureas (median [IQR] follow-up time, 5.1 [2.9-7.8] years) during which 350 cholangiocarcinoma events occurred. Use of DPP4 inhibitors, compared with sulfonylureas, was not associated with a statistically significant increase in risk of cholangiocarcinoma (incidence rate 26 vs 23 per 100,000 person-years; adjusted HR, 1.15 [95% CI 0.90, 1.46]; absolute rate difference 3 [95% CI -3, 10] events per 100,000 person-years). The main analyses of GLP-1-receptor agonists included 1,036,587 person-years of follow-up from 96,813 patients receiving GLP-1-receptor agonists (median [IQR] follow-up time, 4.4 [2.4-6.9] years) and 142,578 patients receiving sulfonylureas (median [IQR] follow-up time, 5.5 [3.2-8.1] years) during which 249 cholangiocarcinoma events occurred. Use of GLP-1-receptor agonists was not associated with a statistically significant increase in risk of cholangiocarcinoma (incidence rate 26 vs 23 per 100,000 person-years; adjusted HR, 1.25 [95% CI 0.89, 1.76]; absolute rate difference 3 [95% CI -5, 13] events per 100,000 patient-years). CONCLUSIONS/INTERPRETATION: In this analysis using nationwide data from three countries, use of DPP4 inhibitors and GLP-1-receptor agonists, compared with sulfonylureas, was not associated with a significantly increased risk of cholangiocarcinoma.

Plasma Proteomics of Renal Function: A Transethnic Meta-Analysis and Mendelian Randomization Study.

BACKGROUND: Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed. METHODS: A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR. RESULTS: In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR. CONCLUSIONS: In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

Metabolic syndrome and the plasma proteome: from association to causation.

BACKGROUND: The metabolic syndrome (MetS), defined by the simultaneous clustering of cardio-metabolic risk factors, is a significant worldwide public health burden with an estimated 25% prevalence worldwide. The pathogenesis of MetS is not entirely clear and the use of molecular level data could help uncover common pathogenic pathways behind the observed clustering. METHODS: Using a highly multiplexed aptamer-based affinity proteomics platform, we examined associations between plasma proteins and prevalent and incident MetS in the KORA cohort (n = 998) and replicated our results for prevalent MetS in the HUNT3 study (n = 923). We applied logistic regression models adjusted for age, sex, smoking status, and physical activity. We used the bootstrap ranking algorithm of least absolute shrinkage and selection operator (LASSO) to select a predictive model from the incident MetS associated proteins and used area under the curve (AUC) to assess its performance. Finally, we investigated the causal effect of the replicated proteins on MetS using two-sample Mendelian randomization. RESULTS: Prevalent MetS was associated with 116 proteins, of which 53 replicated in HUNT. These included previously reported proteins like leptin, and new proteins like NTR domain-containing protein 2 and endoplasmic reticulum protein 29. Incident MetS was associated with 14 proteins in KORA, of which 13 overlap the prevalent MetS associated proteins with soluble advanced glycosylation end product-specific receptor (sRAGE) being unique to incident MetS. The LASSO selected an eight-protein predictive model with an (AUC = 0.75; 95% CI = 0.71-0.79) in KORA. Mendelian randomization suggested causal effects of three proteins on MetS, namely apolipoprotein E2 (APOE2) (Wald-Ratio = - 0.12, Wald-p = 3.63e-13), apolipoprotein B (APOB) (Wald-Ratio = - 0.09, Wald-p = 2.54e-04) and proto-oncogene tyrosine-protein kinase receptor (RET) (Wald-Ratio = 0.10, Wald-p = 5.40e-04). CONCLUSIONS: Our findings offer new insights into the plasma proteome underlying MetS and identify new protein associations. We reveal possible casual effects of APOE2, APOB and RET on MetS. Our results highlight protein candidates that could potentially serve as targets for prevention and therapy.

Deciphering the Plasma Proteome of Type 2 Diabetes.

With an estimated prevalence of 463 million affected, type 2 diabetes represents a major challenge to health care systems worldwide. Analyzing the plasma proteomes of individuals with type 2 diabetes may illuminate hitherto unknown functional mechanisms underlying disease pathology. We assessed the associations between type 2 diabetes and >1,000 plasma proteins in the Cooperative Health Research in the Region of Augsburg (KORA) F4 cohort (n = 993, 110 cases), with subsequent replication in the third wave of the Nord-Trøndelag Health Study (HUNT3) cohort (n = 940, 149 cases). We computed logistic regression models adjusted for age, sex, BMI, smoking status, and hypertension. Additionally, we investigated associations with incident type 2 diabetes and performed two-sample bidirectional Mendelian randomization (MR) analysis to prioritize our results. Association analysis of prevalent type 2 diabetes revealed 24 replicated proteins, of which 8 are novel. Proteins showing association with incident type 2 diabetes were aminoacylase-1, growth hormone receptor, and insulin-like growth factor-binding protein 2. Aminoacylase-1 was associated with both prevalent and incident type 2 diabetes. MR analysis yielded nominally significant causal effects of type 2 diabetes on cathepsin Z and rennin, both known to have roles in the pathophysiological pathways of cardiovascular disease, and of sex hormone-binding globulin on type 2 diabetes. In conclusion, our high-throughput proteomics study replicated previously reported type 2 diabetes-protein associations and identified new candidate proteins possibly involved in the pathogenesis of type 2 diabetes.

Use of sodium-glucose co-transporter 2 inhibitors and risk of serious renal events: Scandinavian cohort study.

OBJECTIVE: To assess the association between use of sodium-glucose co-transporter 2 (SGLT2) inhibitors and risk of serious renal events in data from routine clinical practice. DESIGN: Cohort study using an active comparator, new user design and nationwide register data. SETTING: Sweden, Denmark, and Norway, 2013-18. PARTICIPANTS: Cohort of 29 887 new users of SGLT2 inhibitors (follow-up time: dapagliflozin 66.1%; empagliflozin 32.6%; canagliflozin 1.3%) and 29 887 new users of an active comparator, dipeptidyl peptidase-4 inhibitors, matched 1:1 on the basis of a propensity score with 57 variables. Mean follow-up time was 1.7 (SD 1.0) years. EXPOSURES: SGLT2 inhibitors versus dipeptidyl peptidase-4 inhibitors, defined by filled prescriptions and analysed according to intention to treat. MAIN OUTCOME MEASURES: The main outcome was serious renal events, a composite including renal replacement therapy, death from renal causes, and hospital admission for renal events. Secondary outcomes were the individual components of the main outcome. RESULTS: The mean age of the study population was 61.3 (SD 10.5) years; 11 108 (19%) had cardiovascular disease, and 1974 (3%) had chronic kidney disease. Use of SGLT2 inhibitors, compared with dipeptidyl peptidase-4 inhibitors, was associated with a reduced risk of serious renal events (2.6 events per 1000 person years versus 6.2 events per 1000 person years; hazard ratio 0.42 (95% confidence interval 0.34 to 0.53); absolute difference -3.6 (-4.4 to -2.8) events per 1000 person years). In secondary outcome analyses, the hazard ratio for use of SGLT2 inhibitors versus dipeptidyl peptidase-4 inhibitors was 0.32 (0.22 to 0.47) for renal replacement therapy, 0.41 (0.32 to 0.52) for hospital admission for renal events, and 0.77 (0.26 to 2.23) for death from renal causes. In sensitivity analyses in each of the Swedish and Danish parts of the cohort, the model was further adjusted for glycated haemoglobin and estimated glomerular filtration rate (Sweden and Denmark) and for blood pressure, body mass index, and smoking (Sweden only); in these analyses, the hazard ratio moved from 0.41 (0.26 to 0.66) to 0.50 (0.31 to 0.81) in Sweden and from 0.42 (0.32 to 0.56) to 0.55 (0.41 to 0.74) in Denmark. CONCLUSIONS: In this analysis using nationwide data from three countries, use of SGLT2 inhibitors, compared with dipeptidyl peptidase-4 inhibitors, was associated with a significantly reduced risk of serious renal events.

Plasma protein patterns as comprehensive indicators of health.

Proteins are effector molecules that mediate the functions of genes1,2 and modulate comorbidities3-10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12-16 coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check.