Association between C reactive protein and coronary heart disease: mendelian randomisation analysis based on individual participant data

Role of inflammation in depressive and anxiety disorders, affect, and cognition: genetic and non-genetic findings in the lifelines cohort study

Inflammation is associated with a range of neuropsychiatric symptoms, but the issue of causality remains unclear. We used complementary non-genetic, genetic risk score (GRS), and Mendelian randomization (MR) analyses to examine whether inflammatory markers are associated with affect, depressive and anxiety disorders, and cognition. We tested in ≈55,098 (59% female) individuals from the Dutch Lifelines cohort the concurrent/prospective associations of C-reactive protein (CRP) with: depressive and anxiety disorders; positive/negative affect; and attention, psychomotor speed, episodic memory, and executive functioning at baseline and a follow-up assessment occurring 3.91 years later (SD = 1.21). Additionally, we examined the association between inflammatory GRSs (CRP, interleukin-6 [IL-6], IL-6 receptor [IL-6R and soluble IL-6R (sIL-6R)], glycoprotein acetyls [GlycA]) on these same outcomes (Nmin = 35,300; Nmax = 57,946), followed by MR analysis examining evidence of causality of CRP on outcomes (Nmin=22,154; Nmax = 23,268). In non-genetic analyses, higher CRP was associated with depressive disorder, lower positive/higher negative affect, and worse executive function, attention, and psychomotor speed after adjusting for potential confounders. In genetic analyses, CRPGRS was associated with any anxiety disorder (β = 0.002, p = 0.037) whereas GlycAGRS was associated with major depressive disorder (β = 0.001, p = 0.036). Both CRPGRS (β = 0.006, p = 0.035) and GlycAGRS (β = 0.006, p = 0.049) were associated with greater negative affect. Inflammatory GRSs were not associated with cognition, except sIL-6RGRS which was associated with poorer memory (β = -0.009, p = 0.018). There was a non-significant CRP-anxiety association using MR (β = 0.12; p = 0.054). Genetic and non-genetic analyses provide consistent evidence for an association between CRP and negative affect. These results suggest that inflammation may impact a broad range of trans-diagnostic affective symptoms.

Estimating inflammatory risk in atherosclerotic cardiovascular disease: plaque over plasma?

Inflammation is an important driver of disease in the context of atherosclerosis, and several landmark trials have shown that targeting inflammatory pathways can reduce cardiovascular event rates. However, the high cost and potentially serious adverse effects of anti-inflammatory therapies necessitate more precise patient selection. Traditional biomarkers of inflammation, such as high-sensitivity C-reactive protein, show an association with cardiovascular risk on a population level but do not have specificity for local plaque inflammation. Nowadays, advancements in non-invasive imaging of the vasculature enable direct assessment of vascular inflammation. Positron emission tomography (PET) tracers such as 18F-fluorodeoxyglucose enable detection of metabolic activity of inflammatory cells but are limited by low specificity and myocardial spillover effects. 18F-sodium fluoride is a tracer that identifies active micro-calcification in plaques, indicating vulnerable plaques. Gallium-68 DOTATATE targets pro-inflammatory macrophages by binding to somatostatin receptors, which enhances specificity for plaque inflammation. Coronary computed tomography angiography (CCTA) provides high-resolution images of coronary arteries, identifying high-risk plaque features. Measuring pericoronary adipose tissue attenuation on CCTA represents a novel marker of vascular inflammation. This review examines both established and emerging methods for assessing atherosclerosis-related inflammation, emphasizing the role of advanced imaging in refining risk stratification and guiding personalized therapies. Integrating these imaging modalities with measurements of systemic and molecular biomarkers could shift atherosclerotic cardiovascular disease management towards a more personalized approach.

Relationships of hsCRP to High-Risk Vulnerable Plaque After NSTEMI: Insights From the PROSPECT II Trial

BACKGROUND

Inflammation is a driver of atherosclerosis and susceptibility to cardiovascular events.

OBJECTIVES

The authors sought to evaluate whether high-sensitivity C-reactive protein (hsCRP) levels are associated with the prevalence of high-risk coronary plaques in patients with non-ST-segment elevation myocardial infarction (NSTEMI).

METHODS

PROSPECT (Providing Regional Observations to Study Predictors of Events in the Coronary Tree) II was a multicenter, prospective study enrolling patients with recent myocardial infarction. Following treatment of all flow-limiting lesions, 3-vessel imaging with near-infrared spectroscopy and intravascular ultrasound was used to characterize untreated nonculprit lesions. We investigated the association between baseline hsCRP and plaque morphology (lipid content, plaque burden, lumen area) in 501 NSTEMI patients. hsCRP levels were categorized as low (<1 mg/L), intermediate (1-3 mg/L), or high (>3 mg/L).

RESULTS

The percentages of patients with at least 1 highly lipidic plaque (maximum lipid core burden index for any 4-mm pullback length ≥324.7) increased from 39.4% to 57.2% to 59.3% in the low, intermediate, and high hsCRP groups, respectively (P = 0.01). The proportion of patients with at least 1 highly lipidic plaque with ≥70% burden increased with hsCRP levels from 22.7% to 27.2% to 36.7%, respectively (P = 0.01). Multivariable analyses showed that increasing hsCRP was associated with higher total coronary artery lipid core burden index and plaque volume. Higher hsCRP increased the odds of having any highly lipidic plaque and those with ≥70% plaque burden.

CONCLUSIONS

Among patients with recent NSTEMI, a high baseline hsCRP level was associated with the presence of pan-coronary atherosclerosis and focal high-risk plaques. (PROSPECT II & PROSPECT ABSORB - an Integrated Natural History Study and Randomized Trial; NCT02171065).

High-sensitivity C-reactive protein predicts microalbuminuria progression in essential hypertensive patients: a 3-year follow-up study

OBJECTIVES

To determine the independent effect of high-sensitivity C-reactive protein (hs-CRP) and the combined effects of hs-CRP and other traditional risk factors on microalbuminuria in hypertensive patients during the 3-year follow-up period.

METHODS AND RESULTS

Baseline hs-CRP levels and other risk factors were measured in 280 adults in 2007. In the third year of examination, 199 patients (mean age 62.5 ± 9.5, men 59.3%) were approached for the measurement of microalbuminuria. The subjects were classified into two groups by the median of baseline hs-CRP. Compared to the patients with baseline hs-CRP below the median group ( n  = 99, 50%), the group with baseline hs-CRP above the median ( n  = 100, 50%) had higher urinary albumin-to-creatinine ratio (ACR) ( P  = 0.007) at the end of follow-up period. ACR at the end of follow-up period was significantly correlated with baseline diabetes ( β  = 0.342; P  < 0.001), baseline SBP ( β  = 0.148; P  = 0.02), and baseline log-transformed hs-CRP ( β  = 0.169; P  = 0.01), while adversely correlated with baseline estimated glomerular filtration rate (eGFR) ( β  = -0.163; P  = 0.02) in multivariate stepwise linear analysis. In addition, ACR change during follow-up period was significantly correlated with baseline diabetes ( β  = 0.359; P  < 0.001) and baseline log-transformed hs-CRP ( β  = 0.190; P  = 0.004) in multivariate stepwise linear analysis. The combined effects of baseline hs-CRP and conventional risk factors, such as male sex, diabetes, smoking status, hyperlipidemia, hyperuricemia, and mildly reduced eGFR had a greater risk for microalbuminuria progression. There was no difference in eGFR changes during the follow-up period between two groups.

CONCLUSION

Our findings offer a new piece of evidence on the predictive value of baseline hs-CRP for microalbuminuria progression in essential hypertensive patients, and highlight those who combined with traditional cardiovascular risk factors had a greater risk for developing microalbuminuria.

Inflammatory biomarkers and long-term outcome in young patients three months after a first myocardial infarction

BACKGROUND

Studies on predictive value of circulating inflammatory biomarkers after myocardial infarction (MI) have often been limited by blood sampling only in an acute setting and short follow-up time. We aimed to compare the long-term predictive value of nine inflammatory biomarkers, known to be involved in atherosclerosis, in young patients investigated three months after a first-time MI.

METHODS

Nine biomarkers (high-sensitivity C-reactive protein, interleukin (IL)-6, IL-18, monocyte chemoattractant protein-1, matrix metalloproteinase (MMP)-1, MMP-3, MMP-9, serum amyloid A and tumor necrosis factor-alfa) were sampled in 382 young (<60 years) patients and in age and sex-matched controls, three months after a first-time MI between 1996 and 2000. Swedish national patient registers were used to determine cardiovascular (CV) outcomes during 20 years of follow-up.

RESULTS

In cases, random forest models identified IL-6 as the most important predictor of the primary composite endpoint of death, heart failure (HF) or MI hospitalization, and the separate endpoints death and HF hospitalization. IL-18 was the most important predictor of MI hospitalization. In a Cox regression, the highest tertile of IL-6 was associated with the composite endpoint (HR (95% CI) 1.91 (1.31-2.79)), death (2.38 (1.42-3.98)) and HF hospitalization (2.70 (1.32-5.50)), when adjusting for age, sex and CV risk factors. The highest tertile of IL-18 was associated with MI hospitalization (2.31 (1.08-4.91)) when severity of coronary atherosclerosis was added to the same type of model.

CONCLUSIONS

When nine inflammatory markers involved in atherosclerosis were analyzed three months after the acute event in young MI patients, IL-6 and IL-18 were the most important biomarkers to predict long-term CV outcomes during 20 years of follow-up.

Mendelian Randomization Studies in Atherosclerotic Cardiovascular Diseases

This review aimed to highlight the pivotal role of Mendelian randomization (MR) in advancing atherosclerotic cardiovascular disease (ASCVD) research-a field often hindered by the complexities and limitations of traditional studies. MR, which uses genetic variants as instrumental variables, provides a robust mechanism for inferring causality, offering insights untainted by the confounding factors and biases often prevalent in observational and randomized controlled trials. We explored the significant contributions of MR for elucidating the causal relationship between low-density lipoprotein cholesterol and ASCVD, and analyzed its assumptions and methodological nuances. We discussed issues surrounding instrumental variable selection, pleiotropy, and ethical considerations, in an effort to offer a balanced and insightful analysis. We highlighted the promising integration of MR with emerging technologies and global data sharing, as well as its potential to drive personalized medicine. This review provided a concise yet comprehensive journey into MR's transformative impact on ASCVD research, offering a blend of current insights and challenges, in addition to future prospects. We aimed to serve a valuable resource for those seeking to navigate the intricate pathways of causality and intervention in ASCVD, to aid the development of enhanced understanding and targeted treatment strategies in the future.

Exploring the role of interleukin-6 receptor blockade in epilepsy and associated neuropsychiatric conditions through a mendelian randomization study

BACKGROUND

The interplay between inflammation, immune dysregulation, and the onset of neurological disorders, including epilepsy, has become increasingly recognized. Interleukin (IL)-6, a pro-inflammatory cytokine, is suspected to not only mediate traditional inflammatory pathways but also contribute to neuroinflammatory responses that could underpin neuropsychiatric symptoms and broader psychiatric disorders in epilepsy patients. The role of IL-6 receptor (IL6R) blockade presents an intriguing target for therapeutic intervention due to its potential to attenuate these processes.

AIM

To explore the potential of IL6R blockade in reducing the risk of epilepsy and investigate whether this pathway might also influence associated psychiatric and neuropsychiatric conditions due to neuroinflammation.

METHODS

Mendelian randomization (MR) analysis employing single nucleotide polymorphisms (SNPs) in the vicinity of the IL6R gene (total individuals = 408225) was used to evaluate the putative causal relationship between IL6R blockade and epilepsy (total cases/controls = 12891/312803), focal epilepsy (cases/controls = 7526/399290), and generalized epilepsy (cases/controls = 1413/399287). SNP weights were determined by their effect on C-reactive protein (CRP) levels and integrated using inverse variance-weighted meta-analysis as surrogates for IL6R effects. To address potential outlier and pleiotropic influences, sensitivity analyses were conducted employing a variety of MR methods under different modeling assumptions.

RESULTS

The genetic simulation targeting IL6R blockade revealed a modest but significant reduction in overall epilepsy risk [inverse variance weighting: Odds ratio (OR): 0.827; 95% confidence interval (CI): 0.685-1.000; P = 0.05]. Subtype analysis showed variability, with no significant effect observed in generalized, focal, or specific childhood and juvenile epilepsy forms. Beyond the primary inflammatory marker CRP, the findings also suggested potential non-inflammatory pathways mediated by IL-6 signaling contributing to the neurobiological landscape of epilepsy, hinting at possible links to neuroinflammation, psychiatric symptoms, and associated mental disorders.

CONCLUSION

The investigation underscored a tentative causal relationship between IL6R blockade and decreased epilepsy incidence, likely mediated via complex neuroinflammatory pathways. These results encouraged further in-depth studies involving larger cohorts and multifaceted psychiatric assessments to corroborate these findings and more thoroughly delineate the neuro-psychiatric implications of IL-6 signaling in epilepsy. The exploration of IL6R blockade could herald a novel therapeutic avenue not just for seizure management but also for addressing the broader psychiatric and cognitive disturbances often associated with epilepsy.

C-Reactive Protein: An Important Inflammatory Marker of Coronary Atherosclerotic Disease

Cardiovascular disease (CVD) is the most common cause of death worldwide, with coronary atherosclerotic heart disease (CHD) accounting for the majority of events. Evidence demonstrates that inflammation plays a vital role in the development of CHD. The association between C-reactive protein (CRP), a representative inflammatory biomarker, and atherosclerosis (AS), CHD, and inflammation has attracted attention. Therefore, we conducted an extensive search on PubMed using the aforementioned terms as search criteria and identified a total of 1246 articles published from January 2000 to April 2024. Both review and research-based articles consistently indicate CRP as a risk enhancer for CVD, contributing to the refinement of risk stratification and early identification of apparently healthy at-risk populations. Additionally, CRP reflects disease progression and predicts the prognosis of recurrent cardiovascular events. Anti-inflammatory therapeutic strategies targeting CRP also provide new treatment options for patients. This review focuses on the link between CRP and CHD, highlighting how CRP is involved in the pathological progression of AS and its potential value for clinical applications.

Advancements in risk stratification and management strategies in primary cardiovascular prevention

Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of morbidity and mortality worldwide, highlighting the urgent need for advancements in risk assessment and management strategies. Although significant progress has been made recently, identifying and managing apparently healthy individuals at a higher risk of developing atherosclerosis and those with subclinical atherosclerosis still poses significant challenges. Traditional risk assessment tools have limitations in accurately predicting future events and fail to encompass the complexity of the atherosclerosis trajectory. In this review, we describe novel approaches in biomarkers, genetics, advanced imaging techniques, and artificial intelligence that have emerged to address this gap. Moreover, polygenic risk scores and imaging modalities such as coronary artery calcium scoring, and coronary computed tomography angiography offer promising avenues for enhancing primary cardiovascular risk stratification and personalised intervention strategies. On the other hand, interventions aiming against atherosclerosis development or promoting plaque regression have gained attention in primary ASCVD prevention. Therefore, the potential role of drugs like statins, ezetimibe, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, omega-3 fatty acids, antihypertensive agents, as well as glucose-lowering and anti-inflammatory drugs are also discussed. Since findings regarding the efficacy of these interventions vary, further research is still required to elucidate their mechanisms of action, optimize treatment regimens, and determine their long-term effects on ASCVD outcomes. In conclusion, advancements in strategies addressing atherosclerosis prevention and plaque regression present promising avenues for enhancing primary ASCVD prevention through personalised approaches tailored to individual risk profiles. Nevertheless, ongoing research efforts are imperative to refine these strategies further and maximise their effectiveness in safeguarding cardiovascular health.

Using the global randomization test as a Mendelian randomization falsification test for the exclusion restriction assumption

Mendelian randomization may give biased causal estimates if the instrument affects the outcome not solely via the exposure of interest (violating the exclusion restriction assumption). We demonstrate use of a global randomization test as a falsification test for the exclusion restriction assumption. Using simulations, we explored the statistical power of the randomization test to detect an association between a genetic instrument and a covariate set due to (a) selection bias or (b) horizontal pleiotropy, compared to three approaches examining associations with individual covariates: (i) Bonferroni correction for the number of covariates, (ii) correction for the effective number of independent covariates, and (iii) an r2 permutation-based approach. We conducted proof-of-principle analyses in UK Biobank, using CRP as the exposure and coronary heart disease (CHD) as the outcome. In simulations, power of the randomization test was higher than the other approaches for detecting selection bias when the correlation between the covariates was low (r2 < 0.1), and at least as powerful as the other approaches across all simulated horizontal pleiotropy scenarios. In our applied example, we found strong evidence of selection bias using all approaches (e.g., global randomization test p < 0.002). We identified 51 of the 58 CRP genetic variants as horizontally pleiotropic, and estimated effects of CRP on CHD attenuated somewhat to the null when excluding these from the genetic risk score (OR = 0.96 [95% CI: 0.92, 1.00] versus 0.97 [95% CI: 0.90, 1.05] per 1-unit higher log CRP levels). The global randomization test can be a useful addition to the MR researcher's toolkit.

Life's Essential 8 is inversely associated with high-sensitivity C-reactive protein

Life's Essential 8 (LE8) is a score that includes modifiable risk factors for cardiovascular disease. Four health behaviors (diet, physical activity, nicotine exposure and sleep health) and four health factors (non-HDL cholesterol, blood glucose, blood pressure and body mass index) are included. These modifiable risk factors promote inflammation, and inflammation is one of the biological mechanisms of cardiovascular disease development. Thus, we examined the relationship between cardiovascular health measured by LE8 and low-grade inflammation measured by high-sensitivity C-reactive protein (hs-CRP) in the cross-sectional population-based Swedish CArdioPulmonary bioImage Study (SCAPIS). The study consisted of 28,010 participants between 50 and 64 years (51.5% women, mean age 57.5 years). All individual LE8 components were assigned a score between 0 (unhealthy) and 100 (healthy) points, and a global score was calculated. The association between LE8 scores and high-risk hs-CRP (defined as > 3.0 mg/L) was analyzed using adjusted logistic regression with spline analyses. There was a strong, dose response and inverse association between LE8 scores and levels of hs-CRP. Thus, those with a low LE8 score (= 50.0 points) had 5.8 higher (95% confidence interval [CI] 5.2-6.4) odds ratio (OR) of having high hs-CRP as compared to those with a high LE8 score (= 80.0 points). In conclusion, our findings show strong inverse associations between LE8 scores and levels of hs-CRP.

Obesity-related inflammatory protein signature in cardiovascular clinical outcomes: results from the Gutenberg Health Study

OBJECTIVE

The objective of this study was to investigate whether an obesity-related inflammatory protein signature (OIPS) is associated with adverse cardiovascular events.

METHODS

The Olink Target 96 Inflammation panel was performed in 6662 participants from the population-based Gutenberg Health Study (GHS). The OIPS was selected by a logistic regression model, and its association with cardiovascular outcomes was evaluated by Cox regression analysis. The GHS-derived OIPS was externally validated in the MyoVasc study.

RESULTS

The identified OIPS entailed 21 proteins involved in chemokine activity, tumor necrosis factor (TNF) receptor binding, and growth factor receptor binding. The signature revealed a novel positive association of axis inhibition protein 1 with obesity. The OIPS was associated with increased risk of all-cause and cardiac deaths, major adverse cardiovascular events, and incident coronary artery disease, independent of clinical covariates and established risk instruments. A BMI-stratified analysis confirmed the association of OIPS with increased death in those with obesity and overweight and with increased risk for coronary artery disease in those with obesity. The association of OIPS with increased risk of all-cause and cardiac deaths was validated in the MyoVasc cohort.

CONCLUSIONS

The OIPS showed a significant association with adverse clinical outcomes, particularly in those with overweight and obesity, and represents a promising tool for identifying patients at higher risk for worse cardiovascular outcomes.

Transcriptomic and spatial dissection of human ex vivo right atrial tissue reveals proinflammatory microvascular changes in ischemic heart disease

Cardiovascular disease plays a central role in the electrical and structural remodeling of the right atrium, predisposing to arrhythmias, heart failure, and sudden death. Here, we dissect with single-nuclei RNA sequencing (snRNA-seq) and spatial transcriptomics the gene expression changes in the human ex vivo right atrial tissue and pericardial fluid in ischemic heart disease, myocardial infarction, and ischemic and non-ischemic heart failure using asymptomatic patients with valvular disease who undergo preventive surgery as the control group. We reveal substantial differences in disease-associated gene expression in all cell types, collectively suggesting inflammatory microvascular dysfunction and changes in the right atrial tissue composition as the valvular and vascular diseases progress into heart failure. The data collectively suggest that investigation of human cardiovascular disease should expand to all functionally important parts of the heart, which may help us to identify mechanisms promoting more severe types of the disease.

Role of Inflammation in Depressive and Anxiety Disorders, Affect, and Cognition: Genetic and Non-Genetic Findings in the Lifelines Cohort Study

Background

Low-grade systemic inflammation is implicated in the pathogenesis of various neuropsychiatric conditions affecting mood and cognition. While much of the evidence concerns depression, large-scale population studies of anxiety, affect, and cognitive function are scarce. Importantly, causality remains unclear. We used complementary non-genetic, genetic risk score (GRS), and Mendelian randomization (MR) analyses to examine whether inflammatory markers are associated with affect, depressive and anxiety disorders, and cognitive performance in the Lifelines Cohort; and whether associations are likely to be causal.

Methods

Using data from up to 55,098 (59% female) individuals from the Dutch Lifelines cohort, we tested the cross-sectional and longitudinal associations of C-reactive protein (CRP) with (i) depressive and anxiety disorders; (ii) positive and negative affect scores, and (iii) five cognitive measures assessing attention, psychomotor speed, episodic memory, and executive functioning (figural fluency and working memory). Additionally, we examined the association between inflammatory marker GRSs (CRP, interleukin-6 [IL-6], IL-6 receptor [IL-6R and soluble IL-6R (sIL-6R)], glycoprotein acetyls [GlycA]) on these same outcomes (Nmax=57,946), followed by MR analysis examining evidence of causality of CRP on outcomes (Nmax=23,268). In genetic analyses, all GRSs and outcomes were z-transformed.

Results

In non-genetic analyses, higher CRP was associated with diagnosis of any depressive disorder, lower positive and higher negative affect scores, and worse performance on tests of figural fluency, attention, and psychomotor speed after adjusting for potential confounders, although the magnitude of these associations was small. In genetic analyses, CRPGRS was associated with any anxiety disorder (β=0.002, p=0.037, N=57,047) whereas GlycAGRS was associated with major depressive disorder (β=0.001, p=0.036; N=57,047). Both CRPGRS (β=0.006, p=0.035, N=57,946) and GlycAGRS (β=0.006, p=0.049; N=57,946) were associated with higher negative affect score. Inflammatory marker GRSs were not associated with cognitive performance, except sIL-6RGRS which was associated with poorer memory performance (β=-0.009, p=0.018, N=36,783). Further examination of the CRP-anxiety association using MR provided some weak evidence of causality (β=0.12; p=0.054).

Conclusions

Genetic and non-genetic analyses provide consistent evidence for an association between CRP and negative affect. Genetic analyses suggest that IL-6 signaling could be relevant for memory, and that the association between CRP and anxiety disorders could be causal. These results suggest that dysregulated immune physiology may impact a broad range of trans-diagnostic affective symptoms. However, given the small effect sizes and multiple tests conducted, future studies are required to investigate whether effects are moderated by sub-groups and whether these findings replicate in other cohorts.

Mendelian randomization analysis of 34,497 German Holstein cows to infer causal associations between milk production and health traits

BACKGROUND

Claw diseases and mastitis represent the most important health issues in dairy cattle with a frequently mentioned connection to milk production. Although many studies have aimed at investigating this connection in more detail by estimating genetic correlations, they do not provide information about causality. An alternative is to carry out Mendelian randomization (MR) studies using genetic variants to investigate the effect of an exposure on an outcome trait mediated by genetic variants. No study has yet investigated the causal association of milk yield (MY) with health traits in dairy cattle. Hence, we performed a MR analysis of MY and seven health traits using imputed whole-genome sequence data from 34,497 German Holstein cows. We applied a method that uses summary statistics and removes horizontal pleiotropic variants (having an effect on both traits), which improves the power and unbiasedness of MR studies. In addition, genetic correlations between MY and each health trait were estimated to compare them with the estimates of causal effects that we expected.

RESULTS

All genetic correlations between MY and each health trait were negative, ranging from - 0.303 (mastitis) to - 0.019 (digital dermatitis), which indicates a reduced health status as MY increases. The only non-significant correlation was between MY and digital dermatitis. In addition, each causal association was negative, ranging from - 0.131 (mastitis) to - 0.034 (laminitis), but the number of significant associations was reduced to five nominal and two experiment-wide significant results. The latter were between MY and mastitis and between MY and digital phlegmon. Horizontal pleiotropic variants were identified for mastitis, digital dermatitis and digital phlegmon. They were located within or nearby variants that were previously reported to have a horizontal pleiotropic effect, e.g., on milk production and somatic cell count.

CONCLUSIONS

Our results confirm the known negative genetic connection between health traits and MY in dairy cattle. In addition, they provide new information about causality, which for example points to the negative energy balance mediating the connection between these traits. This knowledge helps to better understand whether the negative genetic correlation is based on pleiotropy, linkage between causal variants for both trait complexes, or indeed on a causal association.

Dementia prevention: the Mendelian randomisation perspective

Understanding the causes of Alzheimer's disease and related dementias remains a challenge. Observational studies investigating dementia risk factors are limited by the pervasive issues of confounding, reverse causation and selection biases. Conducting randomised controlled trials for dementia prevention is often impractical due to the long prodromal phase and the inability to randomise many potential risk factors. In this essay, we introduce Mendelian randomisation as an alternative approach to examine factors that may prevent or delay Alzheimer's disease. Mendelian randomisation is a causal inference method that has successfully identified risk factors and treatments in various other fields. However, applying this method to dementia risk factors has yielded unexpected findings. Here, we consider five potential explanations and provide recommendations to enhance causal inference from Mendelian randomisation studies on dementia. By employing these strategies, we can better understand factors affecting dementia risk.

Advanced detection of coronary artery disease via deep learning analysis of plasma cytokine data

The 2017 World Health Organization Fact Sheet highlights that coronary artery disease is the leading cause of death globally, responsible for approximately 30% of all deaths. In this context, machine learning (ML) technology is crucial in identifying coronary artery disease, thereby saving lives. ML algorithms can potentially analyze complex patterns and correlations within medical data, enabling early detection and accurate diagnosis of CAD. By leveraging ML technology, healthcare professionals can make informed decisions and implement timely interventions, ultimately leading to improved outcomes and potentially reducing the mortality rate associated with coronary artery disease. Machine learning algorithms create non-invasive, quick, accurate, and economical diagnoses. As a result, machine learning algorithms can be employed to supplement existing approaches or as a forerunner to them. This study shows how to use the CNN classifier and RNN based on the LSTM classifier in deep learning to attain targeted "risk" CAD categorization utilizing an evolving set of 450 cytokine biomarkers that could be used as suggestive solid predictive variables for treatment. The two used classifiers are based on these "45" different cytokine prediction characteristics. The best Area Under the Receiver Operating Characteristic curve (AUROC) score achieved is (0.98) for a confidence interval (CI) of 95; the classifier RNN-LSTM used "450" cytokine biomarkers had a great (AUROC) score of 0.99 with a confidence interval of 0.95 the percentage 95, the CNN model containing cytokines received the second best AUROC score (0.92). The RNN-LSTM classifier considerably beats the CNN classifier regarding AUROC scores, as evidenced by a p-value smaller than 7.48 obtained via an independent t-test. As large-scale initiatives to achieve early, rapid, reliable, inexpensive, and accessible individual identification of CAD risk gain traction, robust machine learning algorithms can now augment older methods such as angiography. Incorporating 65 new sensitive cytokine biomarkers can increase early detection even more. Investigating the novel involvement of cytokines in CAD could lead to better risk detection, disease mechanism discovery, and new therapy options.

CT acquisition parameter selection in the real world: impacts on radiation dose and variation amongst 155 institutions

OBJECTIVE

Quantify the relationship between CT acquisition parameters and radiation dose, how often parameters are adjusted in real-world practice, and their degree of contribution to real-world dose distribution. Identify discrepancies between parameters that are impactful in theory and impactful in practice.

METHODS

This study analyses 1.3 million consecutive adult routine abdomen exams performed between November 2015 and Jan 2021 included in the University of California, San Francisco International CT Dose Registry of 155 institutions. We calculated geometric standard deviation (gSD) for five parameters (kV, mAs, spiral pitch, number of phases, scan length) to assess variation in practice. A Gaussian mixed regression model was performed to predict the radiation dose-length product (DLP) using the parameters. Three conceptualizations of "impact" were computed for each parameter. To reflect the theoretical impact, we predict the increase in DLP per 10% (and 15%) increase in the parameter. To reflect the real-world practical impact, we predict the increase in DLP per gSD increase in the parameter.

RESULTS

Among studied examinations, mAs, number of phases, and scan length were frequently manipulated (gSD 1.52-1.70); kV was rarely manipulated (gSD 1.07). Theoretically, kV is the most impactful parameter (29% increase in DLP per 10% increase in kV, versus 5-9% increase for other parameters). In real-world practice, kV is less impactful; for each gSD increase in kV, the DLP increases by 20%, versus 22-69% for other parameters.

CONCLUSION

Despite the potential impact of kV on radiation dose, this parameter is rarely manipulated in common practice and this potential remains untapped.

CLINICAL RELEVANCE STATEMENT

CT beam energy (kV) modulation has the potential to strongly reduce radiation over-dosage to the patient, theoretically more so than similar degrees of modulation in other CT acquisition parameters. Despite this, beam energy modulation rarely occurs in practice, leaving its potential untapped.

KEY POINTS

• The relationship between CT acquisition parameter selection and radiation dose roughly coincided with established theoretical understanding. • CT acquisition parameters differ from each other in frequency and magnitude of manipulation, with beam energy (kV) being rarely manipulated. • Beam energy (kV) has the potential to substantially impact radiation dose, but because it is rarely manipulated, it is the least impactful CT acquisition parameter affecting radiation dose in practice.

Genetic evidence for causal effects of immune dysfunction in psychiatric disorders: where are we?

The question of whether immune dysfunction contributes to risk of psychiatric disorders has long been a subject of interest. To assert this hypothesis a plethora of correlative evidence has been accumulated from the past decades; however, a variety of technical and practical obstacles impeded on a cause-effect interpretation of these data. With the advent of large-scale omics technology and advanced statistical models, particularly Mendelian randomization, new studies testing this old hypothesis are accruing. Here we synthesize these new findings from genomics and genetic causal inference studies on the role of immune dysfunction in major psychiatric disorders and reconcile these new data with pre-omics findings. By reconciling these evidences, we aim to identify key gaps and propose directions for future studies in the field.

Mendelian Randomization as a Tool for Cardiovascular Research: A Review

Importance

Mendelian randomization (MR) is a statistical approach that has become increasingly popular in the field of cardiovascular disease research. It offers a way to infer potentially causal relationships between risk factors and outcomes using observational data, which is particularly important in cases where randomized clinical trials are not feasible or ethical. With the growing availability of large genetic data sets, MR has become a powerful and accessible tool for studying the risk factors for cardiovascular disease.

Observations

MR uses genetic variation associated with modifiable exposures or risk factors to mitigate biases that affect traditional observational study designs. The approach uses genetic variants that are randomly assigned at conception as proxies for exposure to a risk factor, mimicking a randomized clinical trial. By comparing the outcomes of individuals with different genetic variants, researchers may draw causal inferences about the effects of specific risk factors on cardiovascular disease, provided assumptions are met that address (1) the association between each genetic variant and risk factor and (2) the association of the genetic variants with confounders and (3) that the association between each genetic variant and the outcome only occurs through the risk factor. Like other observational designs, MR has limitations, which include weak instruments that are not strongly associated with the exposure of interest, linkage disequilibrium where genetic instruments influence the outcome via correlated rather than direct effects, overestimated genetic associations, and selection and survival biases. In addition, many genetic databases and MR studies primarily include populations genetically similar to European reference populations; improved diversity of participants in these databases and studies is critically needed.

Conclusions and Relevance

This review provides an overview of MR methodology, including assumptions, strengths, and limitations. Several important applications of MR in cardiovascular disease research are highlighted, including the identification of drug targets, evaluation of potential cardiovascular risk factors, as well as emerging methodology. Overall, while MR alone can never prove a causal relationship beyond reasonable doubt, MR offers a rigorous approach for investigating possible causal relationships in observational data and has the potential to transform our understanding of the etiology and treatment of cardiovascular disease.

Incorporating biological and clinical insights into variant choice for Mendelian randomisation: examples and principles

Mendelian randomisation is an accessible and valuable epidemiological approach to provide insight into the causal nature of relationships between risk factor exposures and disease outcomes. However, if performed without critical thought, we may simply have replaced one set of implausible assumptions (no unmeasured confounding or reverse causation) with another set of implausible assumptions (no pleiotropy or other instrument invalidity). The most critical decision to avoid pleiotropy is which genetic variants to use as instrumental variables. Two broad strategies for instrument selection are a biologically motivated strategy and a genome-wide strategy; in general, a biologically motivated strategy is preferred. In this review, we discuss various ways of implementing a biologically motivated selection strategy: using variants in a coding gene region for the exposure or a gene region that encodes a regulator of exposure levels, using a positive control variable and using a biomarker as the exposure rather than its behavioural proxy. In some cases, a genome-wide analysis can provide important complementary evidence, even when its reliability is questionable. In other cases, a biologically-motivated analysis may not be possible. The choice of genetic variants must be informed by biological and functional considerations where possible, requiring collaboration to combine biological and clinical insights with appropriate statistical methodology.

Therapeutic Potential of Downregulated Interleukin-6 Signaling for the Treatment of Chronic Pain: A Mendelian Randomization Study

Introduction

While numerous studies have emphasized the pivotal involvement of the Interleukin 6 (IL-6) pathway in the development of chronic pain, the causal nature of this relationship remains uncertain.

Methods

In this study, we opted to include genetic variants situated within the locus of the IL-6 receptor (IL-6R) that exhibited associations with C-reactive protein (CRP) levels. CRP serves as a downstream effector in the IL-6 pathway. Utilizing these variants as genetic proxies, we aimed to modulate IL-6 signaling. Employing a two-sample Mendelian randomization (MR) approach, we investigated the potential link between the genetic proxy and seven distinct subtypes of chronic pain, categorized based on their corresponding body locations. Moreover, we examined the relationship between chronic pain and an alternative instrument of IL-6 signaling that was weighted based on s-IL-6R levels. Furthermore, we conducted exploratory analyses to estimate the plausible causal association between CRP, gp130, and the subtypes of chronic pain.

Results

Our analysis showed that genetic proxied downregulation of IL-6 signaling, weighted on CRP levels, was linked to a reduced risk of chronic back and knee pain. The sensitivity analyses across various MR methods confirmed the consistency of the findings and showed no evidence of horizontal pleiotropy or heterogeneity. Moreover, the results remained robust with different sets of instrument variables. A genetically increased level of s-IL-6R was also negatively associated with chronic back and knee pain. However, there was no causal relationship between CRP and gp130 with chronic pain.

Conclusion

Based on our findings, there is evidence to suggest a potential causal relationship between IL-6 signaling and chronic back and knee pain. Consequently, the downregulation of IL-6 signaling holds promise as a potential therapeutic target for addressing chronic back and knee pain.

Neutrophil counts and cardiovascular disease

BACKGROUND AND AIMS

Anti-inflammatory trials have shown considerable benefits for cardiovascular disease. High neutrophil counts, an easily accessible inflammation biomarker, are associated with atherosclerosis in experimental studies. This study aimed to investigate the associations between neutrophil counts and risk of nine cardiovascular endpoints using observational and genetic approaches.

METHODS

Observational studies were conducted in the Copenhagen General Population Study (n = 101 730). Genetic studies were firstly performed using one-sample Mendelian randomization (MR) with individual-level data from the UK Biobank (n = 365 913); secondly, two-sample MR analyses were performed using summary-level data from the Blood Cell Consortium (n = 563 085). Outcomes included ischaemic heart disease, myocardial infarction, peripheral arterial disease, ischaemic cerebrovascular disease, ischaemic stroke, vascular-related dementia, vascular dementia, heart failure, and atrial fibrillation.

RESULTS

Observational analyses showed associations between high neutrophil counts with high risks of all outcomes. In the UK Biobank, odds ratios (95% confidence intervals) per 1-SD higher genetically predicted neutrophil counts were 1.15 (1.08, 1.21) for ischaemic heart disease, 1.22 (1.12, 1.34) for myocardial infarction, and 1.19 (1.04, 1.36) for peripheral arterial disease; similar results were observed in men and women separately. In two-sample MR, corresponding estimates were 1.14 (1.05, 1.23) for ischaemic heart disease and 1.11 (1.02, 1.20) for myocardial infarction; multiple sensitivity analyses showed consistent results. No robust associations in two-sample MR analyses were found for other types of leucocytes.

CONCLUSIONS

Observational and genetically determined high neutrophil counts were associated with atherosclerotic cardiovascular disease, supporting that high blood neutrophil counts is a causal risk factor for atherosclerotic cardiovascular disease.

The causal role of C-reactive protein and interleukin-6 on anxiety and depression symptoms and life satisfaction: Mendelian randomisation analyses in the HUNT study

BACKGROUND

Serum levels of C-reactive protein (CRP) and interleukin-6 (IL-6) have been associated with anxiety and depression in cross-sectional and Mendelian randomisation studies, but results regarding the effect size and direction have been mixed. A recent Mendelian Randomisation (MR) study suggested that CRP may decrease and IL-6 may increase anxiety and depression symptoms.

METHODS

Among 68 769 participants of the population-based Trøndelag Health Study (HUNT), we performed cross-sectional observational and one-sample MR analyses of serum CRP and two-sample MR analysis of serum IL-6. The main outcomes were symptoms of anxiety and depression assessed using the Hospital Anxiety and Depression Scale (HADS) and life satisfaction assessed using a seven-level ordinal questionnaire where higher scores indicate lower life satisfaction.

RESULTS

In cross-sectional observational analyses, a doubling in serum CRP level was associated with 0.27% (95% CI -0.20 to 0.75) difference in HADS depression score (HADS-D), -0.77% (95% CI -1.24 to -0.29) difference in HADS anxiety score (HADS-A) and -0.10% (95% CI -0.41 to 0.21) difference in life satisfaction score. In one-sample MR analyses, a doubling in serum CRP was associated with 2.43% (95% CI -0.11 to 5.03) higher HADS-D, 1.94% (95% CI -0.58 to 4.52) higher HADS-A, and 2.00% (95% CI 0.45 to 3.59) higher life satisfaction score. For IL-6, causal point estimates were in the opposite direction, but imprecise and far from conventional criteria for statistical significance.

CONCLUSIONS

Our results do not support a major causal role of serum CRP on anxiety and depression symptoms and life satisfaction, but provides weak evidence that serum CRP may modestly increase anxiety and depression symptoms and reduce life satisfaction. Our findings do not support the recent suggestion that serum CRP may lower anxiety and depression symptoms.

Mendelian randomization for nephrologists

Confounding is a major limitation of observational studies. Mendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. With the emergence of large-scale genome-wide association studies in nephrology over the past decade, MR has become a popular method to establish causal inferences. However, MR is a complex and challenging methodology that requires careful consideration to ensure robust results. This review article aims to summarize the basic concepts of MR, its application and relevance in nephrology, and the methodological challenges and limitations as well as discuss the current guidelines for design and reporting. With reference to a clinically relevant example of examining the causal relationship between the estimated glomerular filtration rate and cancer, this review outlines the key steps to conducting an MR study, including the key considerations and potential pitfalls at each step. These include defining the clinical question, selecting the data sources, identifying and refining appropriate genetic variants by considering linkage disequilibrium and associations with potential confounders, harmonization of variants across data sets, validation of the genetic instrument by assessing its strength, estimation of the causal effects, confirming the validity of the findings, and interpreting and reporting results.

Acute respiratory distress syndrome heterogeneity and the septic ARDS subgroup

Acute respiratory distress syndrome (ARDS) is an acute diffuse inflammatory lung injury characterized by the damage of alveolar epithelial cells and pulmonary capillary endothelial cells. It is mainly manifested by non-cardiogenic pulmonary edema, resulting from intrapulmonary and extrapulmonary risk factors. ARDS is often accompanied by immune system disturbance, both locally in the lungs and systemically. As a common heterogeneous disease in critical care medicine, researchers are often faced with the failure of clinical trials. Latent class analysis had been used to compensate for poor outcomes and found that targeted treatment after subgrouping contribute to ARDS therapy. The subphenotype of ARDS caused by sepsis has garnered attention due to its refractory nature and detrimental consequences. Sepsis stands as the most predominant extrapulmonary cause of ARDS, accounting for approximately 32% of ARDS cases. Studies indicate that sepsis-induced ARDS tends to be more severe than ARDS caused by other factors, leading to poorer prognosis and higher mortality rate. This comprehensive review delves into the immunological mechanisms of sepsis-ARDS, the heterogeneity of ARDS and existing research on targeted treatments, aiming to providing mechanism understanding and exploring ideas for accurate treatment of ARDS or sepsis-ARDS.

The effect of immunomodulatory drugs on aortic stenosis: a Mendelian randomisation analysis

There are currently no approved pharmacological treatment options for aortic stenosis (AS), and there are limited identified drug targets for this chronic condition. It remains unclear whether inflammation plays a role in AS pathogenesis and whether immunomodulation could become a therapeutic target. We evaluated the potentially causal association between inflammation and AS by investigating the genetically proxied effects of tocilizumab (IL6 receptor, IL6R, inhibitor), canakinumab (IL1β inhibitor) and colchicine (β-tubulin inhibitor) through a Mendelian randomisation (MR) approach. Genetic proxies for these drugs were identified as single nucleotide polymorphisms (SNPs) in the gene, enhancer or promoter regions of IL6R, IL1β or β-tubulin gene isoforms, respectively, that were significantly associated with serum C-reactive protein (CRP) in a large European genome-wide association study (GWAS; 575,531 participants). These were paired with summary statistics from a large GWAS of AS in European patients (653,867 participants) to then perform primary inverse-variance weighted random effect and sensitivity MR analyses for each exposure. This analysis showed that genetically proxied tocilizumab was associated with reduced risk of AS (OR 0.56, 95% CI 0.45-0.70 per unit decrease in genetically predicted log-transformed CRP). Genetically proxied canakinumab was not associated with risk of AS (OR 0.80, 95% CI 0.51-1.26), and only one suitable SNP was identified to proxy the effect of colchicine (OR 34.37, 95% CI 1.99-592.89). The finding that genetically proxied tocilizumab was associated with reduced risk of AS is concordant with an inflammatory hypothesis of AS pathogenesis. Inhibition of IL6R may be a promising therapeutic target for AS management.

High residual cardiovascular risk after lipid-lowering: prime time for Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive medicine

As time has come to translate trial results into individualized medical diagnosis and therapy, we analyzed how to minimize residual risk of cardiovascular disease (CVD) by reviewing papers on "residual cardiovascular disease risk". During this review process we found 989 papers that started off with residual CVD risk after initiating statin therapy, continued with papers on residual CVD risk after initiating therapy to increase high-density lipoprotein-cholesterol (HDL-C), followed by papers on residual CVD risk after initiating therapy to decrease triglyceride (TG) levels. Later on, papers dealing with elevated levels of lipoprotein remnants and lipoprotein(a) [Lp(a)] reported new risk factors of residual CVD risk. And as new risk factors are being discovered and new therapies are being tested, residual CVD risk will be reduced further. As we move from CVD risk reduction to improvement of patient management, a paradigm shift from a reductionistic approach towards a holistic approach is required. To that purpose, a personalized treatment dependent on the individual's CVD risk factors including lipid profile abnormalities should be configured, along the line of P5 medicine for each individual patient, i.e., with Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive approaches.

Exploring regression dilution bias using repeat measurements of 2858 variables in ≤49 000 UK Biobank participants

BACKGROUND

Measurement error in exposures and confounders can bias exposure-outcome associations but is rarely considered. We aimed to assess random measurement error of all continuous variables in UK Biobank and explore approaches to mitigate its impact on exposure-outcome associations.

METHODS

Random measurement error was assessed using intraclass correlation coefficients (ICCs) for all continuous variables with repeat measures. Regression calibration was used to correct for random error in exposures and confounders, using the associations of red blood cell distribution width (RDW), C-reactive protein (CRP) and 25-hydroxyvitamin D [25(OH)D] with mortality as illustrative examples.

RESULTS

The 2858 continuous variables with repeat measures varied in sample size from 109 to 49 121. They fell into three groups: (i) baseline visit [529 variables; median (interquartile range) ICC = 0.64 (0.57, 0.83)]; (ii) online diet by 24-h recall [22 variables; 0.35 (0.30, 0.40)] and (iii) imaging measures [2307 variables; 0.85 (0.73, 0.94)]. Highest ICCs were for anthropometric and medical history measures, and lowest for dietary and heart magnetic resonance imaging.The ICCs (95% confidence interval) for RDW, CRP and 25(OH)D were 0.52 (0.51, 0.53), 0.29 (0.27, 0.30) and 0.55 (0.54, 0.56), respectively. Higher RDW and levels of CRP were associated with higher risk of all-cause mortality, and higher concentration of 25(OH)D with lower risk. After correction for random measurement error in the main exposure, the associations all strengthened. Confounder correction did not influence estimates.

CONCLUSIONS

Random measurement error varies widely and is often non-negligible. For UK Biobank we provide relevant statistics and adaptable code to help other researchers explore and correct for this.

Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study

BACKGROUND

Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic information to avoid confounding via Mendelian randomisation (MR).

METHODS

We used the European UK Biobank subcohort ([Formula: see text]), the mental health questionnaire (MHQ) and clinical records. For treatment resistance, a previously curated phenotype based on general practitioner (GP) records and prescription data was employed. We applied univariable and multivariable MR models to genetically predict the exposures and assess their causal contribution to a range of depression outcomes. We used a range of univariable, multivariable and mediation MR models techniques to address our research question with maximum rigour. In addition, we developed a novel statistical procedure to apply pleiotropy-robust multivariable MR to one sample data and employed a Bayesian bootstrap procedure to accurately quantify estimate uncertainty in mediation analysis which outperforms standard approaches in sparse binary outcomes. Given the flexibility of the one-sample design, we evaluated age and sex as moderators of the effects.

RESULTS

In univariable MR models, genetically predicted BMI was positively associated with depression outcomes, including MDD ([Formula: see text] ([Formula: see text] CI): 0.133(0.072, 0.205)) and TRD (0.347(0.002, 0.682)), with a larger magnitude in females and with age acting as a moderator of the effect of BMI on severity of depression (0.22(0.050, 0.389)). Multivariable MR analyses suggested an independent causal effect of BMI on TRD not through CRP (0.395(0.004, 0.732)). Our mediation analyses suggested that the effect of CRP on severity of depression was partly mediated by BMI. Individuals with TRD ([Formula: see text]) observationally had higher CRP and BMI compared with individuals with MDD alone and healthy controls.

DISCUSSION

Our work supports the assertion that BMI exerts a causal effect on a range of clinical and questionnaire-based depression phenotypes, with the effect being stronger in females and in younger individuals. We show that this effect is independent of inflammation proxied by CRP levels as the effects of CRP do not persist when jointly estimated with BMI. This is consistent with previous evidence suggesting that overweight contributed to depression even in the absence of any metabolic consequences. It appears that BMI exerts an effect on TRD that persists when we account for BMI influencing MDD.

Protein-metabolite association studies identify novel proteomic determinants of metabolite levels in human plasma

Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.

Association between high-sensitivity C-reactive protein and coronary atherosclerosis in a general middle-aged population

Despite abundant knowledge about the relationship between inflammation and coronary atherosclerosis, it is still unknown whether systemic inflammation measured as high-sensitivity C-reactive protein (hsCRP) is associated with coronary atherosclerosis in a general population. This study aimed to examine the association between hsCRP and coronary computed tomography angiography (CCTA)-detected coronary atherosclerosis in a population-based cohort. Out of 30,154 randomly invited men and women aged 50 to 64 years in the Swedish Cardiopulmonary Bioimage Study (SCAPIS), 25,408 had a technically acceptable CCTA and analysed hsCRP. Coronary atherosclerosis was defined as presence of plaque of any degree in any of 18 coronary segments. HsCRP values were categorised in four groups. Compared with hsCRP below the detection limit, elevated hsCRP (≥ 2.3 mg/L) was weakly associated with any coronary atherosclerosis (OR 1.15, 95% CI 1.07-1.24), coronary diameter stenosis ≥ 50% (OR 1.27, 95% CI 1.09-1.47), ≥ 4 segments involved (OR 1.13, 95% CI 1.01-1.26 ) and severe atherosclerosis (OR 1.33, 95% CI 1.05-1.69) after adjustment for age, sex and traditional risk factors. The associations were attenuated after further adjustment for body mass index (BMI), although elevated hsCRP still associated with noncalcified plaques (OR 1.16, 95% CI 1.02-1.32), proposed to be more vulnerable. In conclusion, the additional value of hsCRP to traditional risk factors in detection of coronary atherosclerosis is low. The association to high-risk noncalcified plaques, although unlikely through a causal pathway, could explain the relationship between hsCRP and clinical coronary events in numerous studies.

Decreased 25-Hydroxy Vitamin D Level Is Associated with All-Cause Mortality in Patients with Type 2 Diabetes at High Cardiovascular Risk

Cardiovascular diseases are among the leading causes of morbidity and mortality, particularly in individuals with type 2 diabetes. There is a need for new biomarkers to improve the prediction of cardiovascular events and overall mortality. We investigated the association of selected atherosclerosis related biomarkers, specifically osteoprotegerin (OPG), 25-hydroxy-vitamin D (25(OH)D), C-reactive protein (CRP), lipopolysaccharide-binding protein (LBP), and asymmetric dimethylarginine (ADMA), with the occurrence of any cardiovascular event or all-cause mortality (primary outcome) during a 5.6-year follow-up of 190 patients with type 2 diabetes. Data were analyzed using logistic regression to adjust for baseline cardiovascular status and cardiovascular risk factors. The primary outcome occurred in 89 participants (46.8%) during the study. When analyzed individually, 25(OH)D, CRP, and LBP significantly predicted the primary outcome in multivariable models. However, in a model that included all biomarkers, only a decreased level of 25(OH)D remained a significant predictor of the primary outcome. Moreover, the level of 25(OH)D significantly predicted all-cause mortality: a reduction of 10 ng/mL was associated with a two-fold increase in all-cause mortality. Our study thus demonstrates that vitamin D deficiency was the strongest factor associated with the primary outcome and all-cause mortality after a 5.6-year follow-up in patients with type 2 diabetes at high cardiovascular risk.

C-Reactive Protein Level and the Genetic Variant rs1130864 in the CRP Gene as Prognostic Factors for 10-Year Cardiovascular Outcome

BACKGROUND

Cardiovascular disease (CVD) is the primary cause of premature death and disability worldwide. There is extensive evidence that inflammation represents an important pathogenetic mechanism in the development and prognosis of CVD. C-reactive protein (CRP) is a potential marker of vascular inflammation and plays a direct role in CVD by promoting vascular inflammation. The objective of this study (ClinTrials.gov identifier: NCT01045070) was to assess the prognostic impact of CRP protein levels and genetic variants of CRP gene events on cardiovascular (CV) outcome (10-year follow-up) in patients suffering from CVD.

METHODS

CVD patients were prospectively included in this study (n = 1002) and followed up (10 years) regarding combined CV endpoint (CV death, death from stroke, myocardial infarction (MI), and stroke/transient ischemic attack (TIA)). CRP protein level (particle-enhanced immunological turbidity test) and genetic variants (rs1130864, rs1417938, rs1800947, rs3093077; polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) after DNA extraction from EDTA-blood) were evaluated.

RESULTS

In survival analyses, increased CRP protein levels of ≥5 mg/L (log-rank test: p < 0.001, Cox regression: p = 0.002, hazard ratio = 1.49) and CT + TT genotype of rs1130864 (log-rank test: p = 0.041; Cox regression: p = 0.103, hazard ratio = 1.21) were associated with a weaker CV prognosis considering combined CV endpoint.

CONCLUSIONS

Elevated CRP level and genetic variant (rs1130864) were proven to provide prognostic value for adverse outcome in CVD patients within the 10-year follow-up period.

Genetically mimicked effects of ASGR1 inhibitors on all-cause mortality and health outcomes: a drug-target Mendelian randomization study and a phenome-wide association study

BACKGROUND

Asialoglycoprotein receptor 1 (ASGR1) is emerging as a potential drug target to reduce low-density lipoprotein (LDL)-cholesterol and coronary artery disease (CAD) risk. Here, we investigated genetically mimicked ASGR1 inhibitors on all-cause mortality and any possible adverse effects.

METHODS

We conducted a drug-target Mendelian randomization study to assess genetically mimicked effects of ASGR1 inhibitors on all-cause mortality and 25 a priori outcomes relevant to lipid traits, CAD, and possible adverse effects, i.e. liver function, cholelithiasis, adiposity and type 2 diabetes. We also performed a phenome-wide association study of 1951 health-related phenotypes to identify any novel effects. Associations found were compared with those for currently used lipid modifiers, assessed using colocalization, and replicated where possible.

RESULTS

Genetically mimicked ASGR1 inhibitors were associated with a longer lifespan (3.31 years per standard deviation reduction in LDL-cholesterol, 95% confidence interval 1.01 to 5.62). Genetically mimicked ASGR1 inhibitors were inversely associated with apolipoprotein B (apoB), triglycerides (TG) and CAD risk. Genetically mimicked ASGR1 inhibitors were positively associated with alkaline phosphatase, gamma glutamyltransferase, erythrocyte traits, insulin-like growth factor 1 (IGF-1) and C-reactive protein (CRP), but were inversely associated with albumin and calcium. Genetically mimicked ASGR1 inhibitors were not associated with cholelithiasis, adiposity or type 2 diabetes. Associations with apoB and TG were stronger for ASGR1 inhibitors compared with currently used lipid modifiers, and most non-lipid effects were specific to ASGR1 inhibitors. The probabilities for colocalization were > 0.80 for most of these associations, but were 0.42 for lifespan and 0.30 for CAD. These associations were replicated using alternative genetic instruments and other publicly available genetic summary statistics.

CONCLUSIONS

Genetically mimicked ASGR1 inhibitors reduced all-cause mortality. Beyond lipid-lowering, genetically mimicked ASGR1 inhibitors increased liver enzymes, erythrocyte traits, IGF-1 and CRP, but decreased albumin and calcium.

Change in adiposity is associated with change in glycoprotein acetyls but not hsCRP in adolescents with severe obesity

BACKGROUND

Obesity-associated chronic inflammation mediates the development of adverse cardiometabolic outcomes. There are sparse data on associations between severe obesity and inflammatory biomarkers in adolescence; most are cross-sectional and limited to acute phase reactants. Here, we investigate associations between adiposity measures and inflammatory biomarkers in children and adolescents with severe obesity both cross-sectionally and longitudinally.

METHODS

From the Childhood Overweight Biorepository of Australia (COBRA) study, a total of n = 262 participants, mean age 11.5 years (SD 3.5) with obesity had measures of adiposity (body mass index, BMI; % above the 95th BMI-centile, %>95th BMI-centile; waist circumference, WC; waist/height ratio, WtH; % total body fat, %BF; % truncal body fat, %TF) and inflammation biomarkers (glycoprotein acetyls, GlycA; high-sensitivity C-Reactive Protein, hsCRP; white blood cell count, WBC; and neutrophil/lymphocyte ratio, NLR) assessed at baseline. Ninety-eight individuals at mean age of 15.9 years (3.7) participated in a follow-up study 5.6 (2.1) years later. Sixty-two individuals had longitudinal data. Linear regression models, adjusted for age and sex for cross-sectional analyses were applied. To estimate longitudinal associations between change in adiposity measures with inflammation biomarkers, models were adjusted for baseline measures of adiposity and inflammation.

RESULTS

All adiposity measures were cross-sectionally associated with GlycA, hsCRP and WBC at both time points. Change in BMI, %>95th BMI-centile, WC, WtH and %TF were associated with concomitant change in GlycA and WBC, but not in hsCRP and NLR.

CONCLUSION

GlycA and WBC but not hsCRP and NLR may be useful in assessing adiposity-related severity of chronic inflammation over time.

Molecular Biomarkers for Cardiometabolic Disease: Risk Assessment in Young Individuals

Cardiometabolic diseases, including cardiovascular disease and diabetes, are major causes of morbidity and mortality worldwide. Despite progress in prevention and treatment, recent trends show a stalling in the reduction of cardiovascular disease morbidity and mortality, paralleled by increasing rates of cardiometabolic disease risk factors in young adults, underscoring the importance of risk assessments in this population. This review highlights the evidence for molecular biomarkers for early risk assessment in young individuals. We examine the utility of traditional biomarkers in young individuals and discuss novel, nontraditional biomarkers specific to pathways contributing to early cardiometabolic disease risk. Additionally, we explore emerging omic technologies and analytical approaches that could enhance risk assessment for cardiometabolic disease.

Downregulation of interleukin 6 signaling might reduce the risk of periodontitis: a drug target Mendelian randomization study

Aim

Interleukin 6 (IL-6) is considered to play a role in the dysbiotic host response in the development of periodontitis. While the inhibition of the IL-6 receptor using monoclonal antibodies is a well-established therapy for some diseases, so far, its potential benefit in patients with periodontitis has not been examined. We tested the association of genetically proxied downregulation of IL-6 signaling with periodontitis to explore whether downregulation of IL-6 signaling could represent a viable treatment target for periodontitis.

Materials and methods

As proxies for IL-6 signaling downregulation, we selected 52 genetic variants in close vicinity of the gene encoding IL-6 receptor that were associated with lower circulating C-reactive protein (CRP) levels in a genome-wide association study (GWAS) of 575 531 participants of European ancestry from the UK Biobank and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Associations with periodontitis were tested with inverse-variance weighted Mendelian randomization in a study of 17 353 cases and 28 210 controls of European descent in the Gene-Lifestyle Interactions in Dental Endpoints (GLIDE) consortium. In addition, the effect of CRP reduction independent of the IL-6 pathway was assessed.

Results

Genetically proxied downregulation of IL-6 signaling was associated with lower odds of periodontitis (odds ratio (OR) = 0.81 per 1-unit decrement in log-CRP levels; 95% confidence interval (CI): [0.66;0.99]; P = 0.0497). Genetically proxied reduction of CRP independent of the IL-6 pathway had a similar effect (OR = 0.81; 95% CI: [0.68; 0.98]; P = 0.0296).

Conclusion

In conclusion, genetically proxied downregulation of IL-6 signaling was associated with lower odds of periodontitis and CRP might be a causal target for the effect of IL-6 on the risk of periodontitis.

Understanding the molecular mechanisms of statin pleiotropic effects

Statins represent the cornerstone of pharmacotherapy for the prevention of atherosclerotic cardiovascular disease. These medications not only reduce low-density lipoprotein cholesterol (LDL-C) via inhibition of 3-hydroxy-3-methylglutarate attached to CoA reductase, the key rate-limiting step in the cholesterol biosynthetic pathway, but also upregulate expression of the low-density lipoprotein receptor, improving serum clearance. Given LDL-C is a causal risk factor for the development of atherosclerosis, these complementary mechanisms largely explain why statin therapy leads to reductions in major adverse cardiovascular events. However, decades of basic and clinical research have suggested that statins may exert other effects independent of LDL-C lowering, termed pleiotropic effects, which have become a topic of debate among the scientific community. While some literature suggests statins may improve plaque stability, reduce inflammation and thrombosis, decrease oxidative stress, and improve endothelial function and vascular tone, other studies have suggested potential harmful pleiotropic effects related to increased risk of muscle-related side effects, diabetes, hemorrhagic stroke, and cognitive decline. Furthermore, the introduction of newer, non-statin LDL-C lowering therapies, including ezetimibe, proprotein convertase subtilisin/Kexin Type 9, and bempedoic acid, have challenged the statin pleiotropy theory. This review aims to provide a historical background on the development of statins, explore the mechanistic underpinnings of statin pleiotropy, review the available literature, and provide up to date examples that suggest statins may exert effects outside of LDL-C lowering and the cardiovascular system.

Proteomic profiling identifies novel independent relationships between inflammatory proteins and myocardial infarction

BACKGROUND

Inflammation has been implicated in the pathogenesis of coronary heart disease, but the relevance and independence of individual inflammatory proteins is uncertain.

OBJECTIVE

To examine the relationships between a spectrum of inflammatory proteins and myocardial infarction (MI).

METHODS AND RESULTS

A panel of 92 inflammatory proteins was assessed using an OLINK multiplex immunoassay among 432 MI cases (diagnosed < 66 years) and 323 controls. Logistic regression was used to estimate associations between individual proteins and MI, after adjustment for established cardiovascular risk factors and medication use, and stepwise regression to identify proteins with independent effects. Machine learning techniques (Boruta analysis and LASSO regression) and bioinformatic resources were used to examine the concordance of results with those obtained by conventional methods and explore the underlying biological processes to inform the validity of the associations. Among the 92 proteins studied, 62 (67%) had plasma concentrations above the lower limit of detection in at least 50% of samples. Of these, 15 individual proteins were significantly associated with MI after covariate adjustment and correction for multiple testing. Five of these 15 proteins (CDCP1, CD6, IL1-8R1, IL-6, and CXCL1) were independently associated with MI, with up to three-fold higher risks of MI per doubling in plasma concentrations. Findings were further validated using machine learning techniques and biologically focused analyses.

CONCLUSIONS

This study, demonstrating independent relationships between five inflammatory proteins and MI, provides important novel insights into the inflammatory hypothesis of MI and the potential utility of proteomic analyses in precision medicine.

Innate Immunity System in Patients With Cardiovascular and Kidney Disease

With a global burden of 844 million, chronic kidney disease (CKD) is now considered a public health priority. Cardiovascular risk is pervasive in this population, and low-grade systemic inflammation is an established driver of adverse cardiovascular outcomes in these patients. Accelerated cellular senescence, gut microbiota-dependent immune activation, posttranslational lipoprotein modifications, neuroimmune interactions, osmotic and nonosmotic sodium accumulation, acute kidney injury, and precipitation of crystals in the kidney and the vascular system all concur in determining the unique severity of inflammation in CKD. Cohort studies documented a strong link between various biomarkers of inflammation and the risk of progression to kidney failure and cardiovascular events in patients with CKD. Interventions targeting diverse steps of the innate immune response may reduce the risk of cardiovascular and kidney disease. Among these, inhibition of IL-1β (interleukin-1 beta) signaling by canakinumab reduced the risk for cardiovascular events in patients with coronary heart disease, and this protection was equally strong in patients with and without CKD. Several old (colchicine) and new drugs targeting the innate immune system, like the IL-6 (interleukin 6) antagonist ziltivekimab, are being tested in large randomized clinical trials to thoroughly test the hypothesis that mitigating inflammation may translate into better cardiovascular and kidney outcomes in patients with CKD.

Mendelian Randomization Implicates Bidirectional Association between Myopia and Primary Open-Angle Glaucoma or Intraocular Pressure

PURPOSE

Observational studies suggest that myopic eyes carry a greater risk of primary open-angle glaucoma (POAG); however, the evidence for this association is inconsistent. This may be the result of confounding factors that arise from myopia that complicate clinical tests for glaucoma. This study used Mendelian randomization (MR) analysis to determine genetic causal associations among myopia, glaucoma, and glaucoma-related traits that overcome the effects of external confounders.

DESIGN

Bidirectional genetic associations between myopia and refractive spherical equivalent (RSE), POAG, and POAG endophenotypes were investigated.

PARTICIPANTS

Data from the largest publicly available genetic banks (n = 216,257-542,934) were analyzed.

METHODS

Multiple MR models and multivariate genomic structural modeling to identify significant mediators for the relationship between myopia and POAG.

MAIN OUTCOME MEASURES

Genetic causal associations between myopia and POAG and POAG endophenotypes.

RESULTS

We found consistent bidirectional genetic associations between myopia and POAG and between myopia and intraocular pressure (IOP) using multiple MR models at Bonferroni-corrected levels of significance. Intraocular pressure showed the most significant mediation effect on RSE and POAG (Sobel test, 0.13; 95% confidence interval, 0.09-0.17; P = 1.37 × 10^-8).

CONCLUSIONS

A strong bidirectional genetic causal link exists between myopia and POAG that is mediated mainly by IOP. Our findings suggest that IOP-lowering treatment for glaucoma may be beneficial in myopic eyes, despite the challenges of establishing a clear clinical diagnosis.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Using genetic association data to guide drug discovery and development: Review of methods and applications

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.

Association of high-sensitivity C-reactive protein and diabetic nephropathy in patients with type 2 diabetes: a Mendelian randomization study

INTRODUCTION

Observational studies support the relationship between C-reactive protein (CRP) level and diabetic nephropathy (DN) in patients with diabetes. The research question regarding whether the relationship between serum high-sensitivity C-reactive protein (hsCRP) level and DN is causal lacks experimental evidence. Therefore, this study aimed to evaluate the causality between hsCRP and DN based on Mendelian randomization (MR) analysis.

RESEARCH DESIGN AND METHODS

A total of 2332 participants with type 2 diabetes from the Taiwan Biobank database was analyzed. Genetic risk scores (GRSs), which comprise four validated CRP loci as two instrumental variables, were calculated as unweighted and weighted scores to evaluate the causal relationship of hsCRP with DN risk. The two-stage regression model was used to estimate OR and 95% CI.

RESULTS

The analyses of the observational study showed that the hsCRP level was significantly associated with DN after multivariate adjustment (adjusted OR 1.15; 95% CI 1.01 to 1.32). Unweighted/weighted GRSs for log-transformed hsCRP satisfied MR assumptions 1 and 3, respectively; that is, a significant association with hsCRP was observed but that with DN was absent (adjusted OR 1.00, 95% CI 0.92 to 1.09; 1.00, 0.72 to 1.39, respectively). The MR analyses demonstrated that a 1-unit increase in the log-transformed genetically predicted hsCRP by unweighted and weighted GRSs was associated with DN, demonstrating ORs of 1.80 (95% CI 1.51 to 2.14) and 1.67 (95% CI 1.40 to 1.98), respectively.

CONCLUSIONS

The current study provided experimental evidence that hsCRP level was causally related to DN. These findings suggest that the elevated hsCRP may be a causal risk factor for DN in patients with type 2 diabetes.

Statistical methods for cis-Mendelian randomization with two-sample summary-level data

Mendelian randomization (MR) is the use of genetic variants to assess the existence of a causal relationship between a risk factor and an outcome of interest. Here, we focus on two-sample summary-data MR analyses with many correlated variants from a single gene region, particularly on cis-MR studies which use protein expression as a risk factor. Such studies must rely on a small, curated set of variants from the studied region; using all variants in the region requires inverting an ill-conditioned genetic correlation matrix and results in numerically unstable causal effect estimates. We review methods for variable selection and estimation in cis-MR with summary-level data, ranging from stepwise pruning and conditional analysis to principal components analysis, factor analysis, and Bayesian variable selection. In a simulation study, we show that the various methods have comparable performance in analyses with large sample sizes and strong genetic instruments. However, when weak instrument bias is suspected, factor analysis and Bayesian variable selection produce more reliable inferences than simple pruning approaches, which are often used in practice. We conclude by examining two case studies, assessing the effects of low-density lipoprotein-cholesterol and serum testosterone on coronary heart disease risk using variants in the HMGCR and SHBG gene regions, respectively.

Therapeutic potential of IL6R blockade for the treatment of sepsis and sepsis-related death: A Mendelian randomisation study

BACKGROUND

Sepsis is characterised by dysregulated, life-threatening immune responses, which are thought to be driven by cytokines such as interleukin 6 (IL-6). Genetic variants in IL6R known to down-regulate IL-6 signalling are associated with improved Coronavirus Disease 2019 (COVID-19) outcomes, a finding later confirmed in randomised trials of IL-6 receptor antagonists (IL6RAs). We hypothesised that blockade of IL6R could also improve outcomes in sepsis.

METHODS AND FINDINGS

We performed a Mendelian randomisation (MR) analysis using single nucleotide polymorphisms (SNPs) in and near IL6R to evaluate the likely causal effects of IL6R blockade on sepsis (primary outcome), sepsis severity, other infections, and COVID-19 (secondary outcomes). We weighted SNPs by their effect on CRP and combined results across them in inverse variance weighted meta-analysis, proxying the effect of IL6RA. Our outcomes were measured in UK Biobank, FinnGen, the COVID-19 Host Genetics Initiative (HGI), and the GenOSept and GainS consortium. We performed several sensitivity analyses to test assumptions of our methods, including utilising variants around CRP and gp130 in a similar analysis. In the UK Biobank cohort (N = 486,484, including 11,643 with sepsis), IL6R blockade was associated with a decreased risk of our primary outcome, sepsis (odds ratio (OR) = 0.80; 95% confidence interval (CI) 0.66 to 0.96, per unit of natural log-transformed CRP decrease). The size of this effect increased with severity, with larger effects on 28-day sepsis mortality (OR = 0.74; 95% CI 0.47 to 1.15); critical care admission with sepsis (OR = 0.48, 95% CI 0.30 to 0.78) and critical care death with sepsis (OR = 0.37, 95% CI 0.14 to 0.98). Similar associations were seen with severe respiratory infection: OR for pneumonia in critical care 0.69 (95% CI 0.49 to 0.97) and for sepsis survival in critical care (OR = 0.22; 95% CI 0.04 to 1.31) in the GainS and GenOSept consortium, although this result had a large degree of imprecision. We also confirm the previously reported protective effect of IL6R blockade on severe COVID-19 (OR = 0.69, 95% CI 0.57 to 0.84) in the COVID-19 HGI, which was of similar magnitude to that seen in sepsis. Sensitivity analyses did not alter our primary results. These results are subject to the limitations and assumptions of MR, which in this case reflects interpretation of these SNP effects as causally acting through blockade of IL6R, and reflect lifetime exposure to IL6R blockade, rather than the effect of therapeutic IL6R blockade.

CONCLUSIONS

IL6R blockade is causally associated with reduced incidence of sepsis. Similar but imprecisely estimated results supported a causal effect also on sepsis related mortality and critical care admission with sepsis. These effects are comparable in size to the effect seen in severe COVID-19, where IL-6 receptor antagonists were shown to improve survival. These data suggest that a randomised trial of IL-6 receptor antagonists in sepsis should be considered.