Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization.

BACKGROUND: Heart failure (HF) is a highly prevalent disorder for which disease mechanisms are incompletely understood. The discovery of disease-associated proteins with causal genetic evidence provides an opportunity to identify new therapeutic targets. METHODS: We investigated the observational and causal associations of 90 cardiovascular proteins, which were measured using affinity-based proteomic assays. First, we estimated the associations of 90 cardiovascular proteins with incident heart failure by means of a fixed-effect meta-analysis of 4 population-based studies, composed of a total of 3019 participants with 732 HF events. The causal effects of HF-associated proteins were then investigated by Mendelian randomization, using cis-protein quantitative loci genetic instruments identified from genomewide association studies in more than 30 000 individuals. To improve the precision of causal estimates, we implemented an Mendelian randomization model that accounted for linkage disequilibrium between instruments and tested the robustness of causal estimates through a multiverse sensitivity analysis that included up to 120 combinations of instrument selection parameters and Mendelian randomization models per protein. The druggability of candidate proteins was surveyed, and mechanism of action and potential on-target side effects were explored with cross-trait Mendelian randomization analysis. RESULTS: Forty-four of ninety proteins were positively associated with risk of incident HF (P<6.0×10-4). Among these, 8 proteins had evidence of a causal association with HF that was robust to multiverse sensitivity analysis: higher CSF-1 (macrophage colony-stimulating factor 1), Gal-3 (galectin-3) and KIM-1 (kidney injury molecule 1) were positively associated with risk of HF, whereas higher ADM (adrenomedullin), CHI3L1 (chitinase-3-like protein 1), CTSL1 (cathepsin L1), FGF-23 (fibroblast growth factor 23), and MMP-12 (matrix metalloproteinase-12) were protective. Therapeutics targeting ADM and Gal-3 are currently under evaluation in clinical trials, and all the remaining proteins were considered druggable, except KIM-1. CONCLUSIONS: We identified 44 circulating proteins that were associated with incident HF, of which 8 showed evidence of a causal relationship and 7 were druggable, including adrenomedullin, which represents a particularly promising drug target. Our approach demonstrates a tractable roadmap for the triangulation of population genomic and proteomic data for the prioritization of therapeutic targets for complex human diseases.

Triangulating evidence from observational and Mendelian randomization studies of ketone bodies for cognitive performance.

BACKGROUND: Ketone bodies (KBs) are an alternative energy supply for brain functions when glucose is limited. The most abundant ketone metabolite, 3-ß-hydroxybutyrate (BOHBUT), has been suggested to prevent or delay cognitive impairment, but the evidence remains unclear. We triangulated observational and Mendelian randomization (MR) studies to investigate the association and causation between KBs and cognitive function. METHODS: In observational analyses of 5506 participants aged ≥ 45 years from the Whitehall II study, we used multiple linear regression to investigate the associations between categorized KBs and cognitive function scores. Two-sample MR was carried out using summary statistics from an in-house KBs meta-analysis between the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium and Kettunen et al. (N = 45,031), and publicly available summary statistics of cognitive performance and Alzheimer's disease (AD) from the Social Science Genetic Association Consortium (N = 257,841), and the International Genomics of Alzheimer's Project (N = 54,162), respectively. Both strong (P < 5 × 10-8) and suggestive (P < 1 × 10-5) sets of instrumental variables for BOHBUT were applied. Finally, we performed cis-MR on OXCT1, a well-known gene for KB catabolism. RESULTS: BOHBUT was positively associated with general cognitive function (ß = 0.26, P = 9.74 × 10-3). In MR analyses, we observed a protective effect of BOHBUT on cognitive performance (inverse variance weighted: ßIVW = 7.89 × 10-2, PIVW = 1.03 × 10-2; weighted median: ßW-Median = 8.65 × 10-2, PW-Median = 9.60 × 10-3) and a protective effect on AD (ßIVW = - 0.31, odds ratio: OR = 0.74, PIVW = 3.06 × 10-2). Cis-MR showed little evidence of therapeutic modulation of OXCT1 on cognitive impairment. CONCLUSIONS: Triangulation of evidence suggests that BOHBUT has a beneficial effect on cognitive performance. Our findings raise the hypothesis that increased BOHBUT may improve general cognitive functions, delaying cognitive impairment and reducing the risk of AD.

Untargeted Metabolomics Identifies Potential Hypertrophic Cardiomyopathy Biomarkers in Carriers of MYBPC3 Founder Variants.

Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease, commonly caused by pathogenic MYBPC3 variants, and a significant cause of sudden cardiac death. Severity is highly variable, with incomplete penetrance among genotype-positive family members. Previous studies demonstrated metabolic changes in HCM. We aimed to identify metabolite profiles associated with disease severity in carriers of MYBPC3 founder variants using direct-infusion high-resolution mass spectrometry in plasma of 30 carriers with a severe phenotype (maximum wall thickness ≥20 mm, septal reduction therapy, congestive heart failure, left ventricular ejection fraction <50%, or malignant ventricular arrhythmia) and 30 age- and sex-matched carriers with no or a mild phenotype. Of the top 25 mass spectrometry peaks selected by sparse partial least squares discriminant analysis, XGBoost gradient boosted trees, and Lasso logistic regression (42 total), 36 associated with severe HCM at a p < 0.05, 20 at p < 0.01, and 3 at p < 0.001. These peaks could be clustered to several metabolic pathways, including acylcarnitine, histidine, lysine, purine and steroid hormone metabolism, and proteolysis. In conclusion, this exploratory case-control study identified metabolites associated with severe phenotypes in MYBPC3 founder variant carriers. Future studies should assess whether these biomarkers contribute to HCM pathogenesis and evaluate their contribution to risk stratification.

Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings.

AIMS/HYPOTHESIS: We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes. METHODS: Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation. RESULTS: We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001). CONCLUSIONS/INTERPRETATION: CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability.

Polygenic risk scores for coronary artery disease and subsequent event risk amongst established cases.

BACKGROUND: There is growing evidence that polygenic risk scores (PRSs) can identify individuals with elevated lifetime risk of coronary artery disease (CAD). Whether they can also be used to stratify the risk of subsequent events among those surviving a first CAD event remain uncertain, with possible biological differences between CAD onset and progression, and the potential for index event bias. METHODS: Using two baseline subsamples of UK Biobank: prevalent CAD cases (N = 10 287) and individuals without CAD (N = 393 108), we evaluated associations between a CAD PRS and incident cardiovascular and fatal outcomes. RESULTS: A 1 SD higher PRS was associated with an increased risk of incident myocardial infarction (MI) in participants without CAD (OR 1.33; 95% CI 1.29, 1.38), but the effect estimate was markedly attenuated in those with prevalent CAD (OR 1.15; 95% CI 1.06, 1.25) and heterogeneity P = 0.0012. Additionally, among prevalent CAD cases, we found an evidence of an inverse association between the CAD PRS and risk of all-cause death (OR 0.91; 95% CI 0.85, 0.98) compared with those without CAD (OR 1.01; 95% CI 0.99, 1.03) and heterogeneity P = 0.0041. A similar inverse association was found for ischaemic stroke [prevalent CAD (OR 0.78; 95% CI 0.67, 0.90); without CAD (OR 1.09; 95% CI 1.04, 1.15), heterogeneity P < 0.001]. CONCLUSIONS: Bias induced by case stratification and survival into UK Biobank may distort the associations of PRS derived from case-control studies or populations initially free of disease. Differentiating between effects of possible biases and genuine biological heterogeneity is a major challenge in disease progression research.

Association of Factor V Leiden With Subsequent Atherothrombotic Events: A GENIUS-CHD Study of Individual Participant Data.

BACKGROUND: Studies examining the role of factor V Leiden among patients at higher risk of atherothrombotic events, such as those with established coronary heart disease (CHD), are lacking. Given that coagulation is involved in the thrombus formation stage on atherosclerotic plaque rupture, we hypothesized that factor V Leiden may be a stronger risk factor for atherothrombotic events in patients with established CHD. METHODS: We performed an individual-level meta-analysis including 25 prospective studies (18 cohorts, 3 case-cohorts, 4 randomized trials) from the GENIUS-CHD (Genetics of Subsequent Coronary Heart Disease) consortium involving patients with established CHD at baseline. Participating studies genotyped factor V Leiden status and shared risk estimates for the outcomes of interest using a centrally developed statistical code with harmonized definitions across studies. Cox proportional hazards regression models were used to obtain age- and sex-adjusted estimates. The obtained estimates were pooled using fixed-effect meta-analysis. The primary outcome was composite of myocardial infarction and CHD death. Secondary outcomes included any stroke, ischemic stroke, coronary revascularization, cardiovascular mortality, and all-cause mortality. RESULTS: The studies included 69 681 individuals of whom 3190 (4.6%) were either heterozygous or homozygous (n=47) carriers of factor V Leiden. Median follow-up per study ranged from 1.0 to 10.6 years. A total of 20 studies with 61 147 participants and 6849 events contributed to analyses of the primary outcome. Factor V Leiden was not associated with the combined outcome of myocardial infarction and CHD death (hazard ratio, 1.03 [95% CI, 0.92-1.16]; I2=28%; P-heterogeneity=0.12). Subgroup analysis according to baseline characteristics or strata of traditional cardiovascular risk factors did not show relevant differences. Similarly, risk estimates for the secondary outcomes including stroke, coronary revascularization, cardiovascular mortality, and all-cause mortality were also close to identity. CONCLUSIONS: Factor V Leiden was not associated with increased risk of subsequent atherothrombotic events and mortality in high-risk participants with established and treated CHD. Routine assessment of factor V Leiden status is unlikely to improve atherothrombotic events risk stratification in this population.

Lipid lowering and Alzheimer disease risk: A mendelian randomization study.

OBJECTIVE: To examine whether genetic variation affecting the expression or function of lipid-lowering drug targets is associated with Alzheimer disease (AD) risk, to evaluate the potential impact of long-term exposure to corresponding therapeutics. METHODS: We conducted Mendelian randomization analyses using variants in genes that encode the protein targets of several approved lipid-lowering drug classes: HMGCR (encoding the target for statins), PCSK9 (encoding the target for PCSK9 inhibitors, eg, evolocumab and alirocumab), NPC1L1 (encoding the target for ezetimibe), and APOB (encoding the target of mipomersen). Variants were weighted by associations with low-density lipoprotein cholesterol (LDL-C) using data from lipid genetics consortia (n up to 295,826). We meta-analyzed Mendelian randomization estimates for regional variants weighted by LDL-C on AD risk from 2 large samples (total n = 24,718 cases, 56,685 controls). RESULTS: Models for HMGCR, APOB, and NPC1L1 did not suggest that the use of related lipid-lowering drug classes would affect AD risk. In contrast, genetically instrumented exposure to PCSK9 inhibitors was predicted to increase AD risk in both of the AD samples (combined odds ratio per standard deviation lower LDL-C inducible by the drug target = 1.45, 95% confidence interval = 1.23-1.69). This risk increase was opposite to, although more modest than, the degree of protection from coronary artery disease predicted by these same methods for PCSK9 inhibition. INTERPRETATION: We did not identify genetic support for the repurposing of statins, ezetimibe, or mipomersen for AD prevention. Notwithstanding caveats to this genetic evidence, pharmacovigilance for AD risk among users of PCSK9 inhibitors may be warranted. ANN NEUROL 2020;87:30-39.

Association between 8 P-glycoprotein (MDR1/ABCB1) gene polymorphisms and antipsychotic drug-induced hyperprolactinaemia.

INTRODUCTION: Hyperprolactinaemia, a common adverse effect of antipsychotic drugs, is primarily linked to blockade of dopamine D2 receptors in the pituitary gland. Certain antipsychotic drugs, such as, for example risperidone and paliperidone, are more likely to induce hyperprolactinaemia compared to others. This effect is probably caused by a relatively high blood/brain concentration ratio, a consequence of being a substrate of P-glycoprotein. Genetic variants of P-glycoprotein with changed functional activity might influence the potential of risperidone and paliperidone to cause hyperprolactinaemia as the altered blood/brain concentration ratio would lead to a reduced therapeutic drug level within essential brain areas making dose adaptations necessary. This increases exposure of dopamine D2 receptors within the pituitary gland. AIMS: To investigate possible associations between MDR1/ABCB1 gene polymorphisms and antipsychotic drug-induced hyperprolactinaemia in Russian patients with schizophrenia and to determine possible differences between risperidone/paliperidone and other antipsychotics. METHODS: In total, 446 patients with schizophrenia were included from 3 psychiatric hospitals in Siberia. Blood samples were obtained in a cross-sectional study design for DNA extraction and prolactin measurement. Associations between hyperprolactinaemia and 8 MDR1/ABCB1 gene-polymorphisms were assessed using logistic regression analysis accounting for covariates. The analysis was repeated in a patient subgroup using risperidone or paliperidone. RESULTS: We did not observe an association between any of the 8 single nucleotide polymorphisms and the prevalence of antipsychotic-induced hyperprolactinaemia in the total patient population. However, in the risperidone/paliperidone subgroup, the single nucleotide polymorphism rs2032582 (G2677T) was found to be negatively associated with risperidone/paliperidone-induced hyperprolactinaemia. CONCLUSION: This study revealed a significant association between the ABCB1 gene polymorphism rs2032582 (G2677T) and risperidone/paliperidone-induced hyperprolactinaemia.

PCSK9 monoclonal antibodies for the primary and secondary prevention of cardiovascular disease.

BACKGROUND: Despite the availability of effective drug therapies that reduce low-density lipoprotein (LDL)-cholesterol (LDL-C), cardiovascular disease (CVD) remains an important cause of mortality and morbidity. Therefore, additional LDL-C reduction may be warranted, especially for people who are unresponsive to, or unable to take, existing LDL-C-reducing therapies. By inhibiting the proprotein convertase subtilisin/kexin type 9 (PCSK9) enzyme, monoclonal antibodies (PCSK9 inhibitors) reduce LDL-C and CVD risk. OBJECTIVES: Primary To quantify the effects of PCSK9 inhibitors on CVD, all-cause mortality, myocardial infarction, and stroke, compared to placebo or active treatment(s) for primary and secondary prevention. Secondary To quantify the safety of PCSK9 inhibitors, with specific focus on the incidence of influenza, hypertension, type 2 diabetes, and cancer, compared to placebo or active treatment(s) for primary and secondary prevention. SEARCH METHODS: We identified studies by systematically searching CENTRAL, MEDLINE, Embase, and Web of Science in December 2019. We also searched ClinicalTrials.gov and the International Clinical Trials Registry Platform in August 2020 and screened the reference lists of included studies. This is an update of the review first published in 2017. SELECTION CRITERIA: All parallel-group and factorial randomised controlled trials (RCTs) with a follow-up of at least 24 weeks were eligible. DATA COLLECTION AND ANALYSIS: Two review authors independently reviewed and extracted data. Where data were available, we calculated pooled effect estimates. We used GRADE to assess certainty of evidence and in 'Summary of findings' tables. MAIN RESULTS: We included 24 studies with data on 60,997 participants. Eighteen trials randomised participants to alirocumab and six to evolocumab. All participants received background lipid-lowering treatment or lifestyle counselling. Six alirocumab studies used  an active treatment comparison group (the remaining used placebo), compared to three evolocumab active comparison trials. Alirocumab compared with placebo decreased the risk of CVD events, with an absolute risk difference (RD) of -2% (odds ratio (OR) 0.87, 95% confidence interval (CI) 0.80 to 0.94; 10 studies, 23,868 participants; high-certainty evidence), decreased the risk of mortality (RD -1%; OR 0.83, 95% CI 0.72 to 0.96; 12 studies, 24,797 participants; high-certainty evidence), and MI (RD -2%; OR 0.86, 95% CI 0.79 to 0.94; 9 studies, 23,352 participants; high-certainty evidence) and for any stroke (RD 0%; OR 0.73, 95% CI 0.58 to 0.91; 8 studies, 22,835 participants; high-certainty evidence). Compared to active treatment the alirocumab effects, for CVD, the RD was 1% (OR 1.37, 95% CI 0.65 to 2.87; 3 studies, 1379 participants; low-certainty evidence); for mortality, RD was -1% (OR 0.51, 95% CI 0.18 to 1.40; 5 studies, 1333 participants; low-certainty evidence); for MI, RD was 1% (OR 1.45, 95% CI 0.64 to 3.28, 5 studies, 1734 participants; low-certainty evidence); and for any stroke, RD was less than 1% (OR 0.85, 95% CI 0.13 to 5.61; 5 studies, 1734 participants; low-certainty evidence). Compared to placebo the evolocumab, for CVD, the RD was -2% (OR 0.84, 95% CI 0.78 to 0.91; 3 studies, 29,432 participants; high-certainty evidence); for mortality, RD was less than 1% (OR 1.04, 95% CI 0.91 to 1.19; 3 studies, 29,432 participants; high-certainty evidence); for MI, RD was -1% (OR 0.72, 95% CI 0.64 to 0.82; 3 studies, 29,432 participants; high-certainty evidence); and for any stroke RD was less than -1% (OR 0.79, 95% CI 0.65 to 0.94; 2 studies, 28,531 participants; high-certainty evidence).  Compared to active treatment, the evolocumab effects, for any CVD event RD was less than -1% (OR 0.66, 95% CI 0.14 to 3.04; 1 study, 218 participants; very low-certainty evidence); for all-cause mortality, the RD was less than 1% (OR 0.43, 95% CI 0.14 to 1.30; 3 studies, 5223 participants; very low-certainty evidence); and for MI, RD was less than 1% (OR 0.66, 95% CI 0.23 to 1.85; 3 studies, 5003 participants; very low-certainty evidence). There were insufficient data on any stroke.  AUTHORS' CONCLUSIONS: The evidence for the clinical endpoint effects of  evolocumab and alirocumab were graded as high. There is a strong evidence base to prescribe PCSK9 monoclonal antibodies to people who might not be eligible for other lipid-lowering drugs, or to people who cannot meet their lipid goals on more traditional therapies, which was the main patient population of the available trials.  The evidence base of PCSK9 inhibitors compared with active treatment is much weaker (low very- to low-certainty evidence) and it is unclear whether evolocumab or alirocumab might be effectively used as replacement therapies. Related, most of the available studies preferentially enrolled people with either established CVD or at a high risk already, and evidence in low- to medium-risk settings is minimal. Finally, there is very limited evidence on any potential safety issues of both evolocumab and alirocumab. While the current evidence synthesis does not reveal any adverse signals, neither does it provide evidence against such signals. This suggests careful consideration of alternative lipid lowering treatments before prescribing PCSK9 inhibitors.

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9.

BACKGROUND: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9. METHODS: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration. RESULTS: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable. CONCLUSIONS: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.

PCSK9 monoclonal antibodies for the primary and secondary prevention of cardiovascular disease.

BACKGROUND: Despite the availability of effective drug therapies that reduce low-density lipoprotein (LDL)-cholesterol (LDL-C), cardiovascular disease (CVD) remains an important cause of mortality and morbidity. Therefore, additional LDL-C reduction may be warranted, especially for patients who are unresponsive to, or unable to take, existing LDL-C-reducing therapies. By inhibiting the proprotein convertase subtilisin/kexin type 9 (PCSK9) enzyme, monoclonal antibodies (PCSK9 inhibitors) may further reduce LDL-C, potentially reducing CVD risk as well. OBJECTIVES: Primary To quantify short-term (24 weeks), medium-term (one year), and long-term (five years) effects of PCSK9 inhibitors on lipid parameters and on the incidence of CVD. Secondary To quantify the safety of PCSK9 inhibitors, with specific focus on the incidence of type 2 diabetes, cognitive function, and cancer. Additionally, to determine if specific patient subgroups were more or less likely to benefit from the use of PCSK9 inhibitors. SEARCH METHODS: We identified studies by systematically searching the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and Web of Science. We also searched Clinicaltrials.gov and the International Clinical Trials Registry Platform and screened the reference lists of included studies. We identified the studies included in this review through electronic literature searches conducted up to May 2016, and added three large trials published in March 2017. SELECTION CRITERIA: All parallel-group and factorial randomised controlled trials (RCTs) with a follow-up time of at least 24 weeks were eligible. DATA COLLECTION AND ANALYSIS: Two review authors independently reviewed and extracted data. When data were available, we calculated pooled effect estimates. MAIN RESULTS: We included 20 studies with data on 67,237 participants (median age 61 years; range 52 to 64 years). Twelve trials randomised participants to alirocumab, three trials to bococizumab, one to RG7652, and four to evolocumab. Owing to the small number of trials using agents other than alirocumab, we did not differentiate between types of PCSK9 inhibitors used. We compared PCSK9 inhibitors with placebo (thirteen RCTs), ezetimibe (two RCTs) or ezetimibe and statins (five RCTs).Compared with placebo, PCSK9 inhibitors decreased LDL-C by 53.86% (95% confidence interval (CI) 58.64 to 49.08; eight studies; 4782 participants; GRADE: moderate) at 24 weeks; compared with ezetimibe, PCSK9 inhibitors decreased LDL-C by 30.20% (95% CI 34.18 to 26.23; two studies; 823 participants; GRADE: moderate), and compared with ezetimibe and statins, PCSK9 inhibitors decreased LDL-C by 39.20% (95% CI 56.15 to 22.26; five studies; 5376 participants; GRADE: moderate).Compared with placebo, PCSK9 inhibitors decreased the risk of CVD events, with a risk difference (RD) of 0.91% (odds ratio (OR) of 0.86, 95% CI 0.80 to 0.92; eight studies; 59,294 participants; GRADE: moderate). Compared with ezetimibe and statins, PCSK9 inhibitors appeared to have a stronger protective effect on CVD risk, although with considerable uncertainty (RD 1.06%, OR 0.45, 95% CI 0.27 to 0.75; three studies; 4770 participants; GRADE: very low). No data were available for the ezetimibe only comparison. Compared with placebo, PCSK9 probably had little or no effect on mortality (RD 0.03%, OR 1.02, 95% CI 0.91 to 1.14; 12 studies; 60,684 participants; GRADE: moderate). Compared with placebo, PCSK9 inhibitors increased the risk of any adverse events (RD 1.54%, OR 1.08, 95% CI 1.04 to 1.12; 13 studies; 54,204 participants; GRADE: low). Similar effects were observed for the comparison of ezetimibe and statins: RD 3.70%, OR 1.18, 95% CI 1.05 to 1.34; four studies; 5376 participants; GRADE: low. Clinical event data were unavailable for the ezetimibe only comparison. AUTHORS' CONCLUSIONS: Over short-term to medium-term follow-up, PCSK9 inhibitors reduced LDL-C. Studies with medium-term follow-up time (longest median follow-up recorded was 26 months) reported that PCSK9 inhibitors (compared with placebo) decreased CVD risk but may have increased the risk of any adverse events (driven by SPIRE-1 and -2 trials). Available evidence suggests that PCSK9 inhibitor use probably leads to little or no difference in mortality. Evidence on relative efficacy and safety when PCSK9 inhibitors were compared with active treatments was of low to very low quality (GRADE); follow-up times were short and events were few. Large trials with longer follow-up are needed to evaluate PCSK9 inhibitors versus active treatments as well as placebo. Owing to the predominant inclusion of high-risk patients in these studies, applicability of results to primary prevention is limited. Finally, estimated risk differences indicate that PCSK9 inhibitors only modestly change absolute risks (often to less than 1%).

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis.

BACKGROUND: Higher circulating levels of the branched-chain amino acids (BCAAs; i.e., isoleucine, leucine, and valine) are strongly associated with higher type 2 diabetes risk, but it is not known whether this association is causal. We undertook large-scale human genetic analyses to address this question. METHODS AND FINDINGS: Genome-wide studies of BCAA levels in 16,596 individuals revealed five genomic regions associated at genome-wide levels of significance (p < 5 × 10-8). The strongest signal was 21 kb upstream of the PPM1K gene (beta in standard deviations [SDs] of leucine per allele = 0.08, p = 3.9 × 10-25), encoding an activator of the mitochondrial branched-chain alpha-ketoacid dehydrogenase (BCKD) responsible for the rate-limiting step in BCAA catabolism. In another analysis, in up to 47,877 cases of type 2 diabetes and 267,694 controls, a genetically predicted difference of 1 SD in amino acid level was associated with an odds ratio for type 2 diabetes of 1.44 (95% CI 1.26-1.65, p = 9.5 × 10-8) for isoleucine, 1.85 (95% CI 1.41-2.42, p = 7.3 × 10-6) for leucine, and 1.54 (95% CI 1.28-1.84, p = 4.2 × 10-6) for valine. Estimates were highly consistent with those from prospective observational studies of the association between BCAA levels and incident type 2 diabetes in a meta-analysis of 1,992 cases and 4,319 non-cases. Metabolome-wide association analyses of BCAA-raising alleles revealed high specificity to the BCAA pathway and an accumulation of metabolites upstream of branched-chain alpha-ketoacid oxidation, consistent with reduced BCKD activity. Limitations of this study are that, while the association of genetic variants appeared highly specific, the possibility of pleiotropic associations cannot be entirely excluded. Similar to other complex phenotypes, genetic scores used in the study captured a limited proportion of the heritability in BCAA levels. Therefore, it is possible that only some of the mechanisms that increase BCAA levels or affect BCAA metabolism are implicated in type 2 diabetes. CONCLUSIONS: Evidence from this large-scale human genetic and metabolomic study is consistent with a causal role of BCAA metabolism in the aetiology of type 2 diabetes.

Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

BACKGROUND: Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. METHODS: We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. RESULTS: At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. CONCLUSION: In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

Prioritising genetic findings for drug target identification and validation.

The decreasing costs of high-throughput genetic sequencing and increasing abundance of sequenced genome data have paved the way for the use of genetic data in identifying and validating potential drug targets. However, the number of identified potential drug targets is often prohibitively large to experimentally evaluate in wet lab experiments, highlighting the need for systematic approaches for target prioritisation. In this review, we discuss principles of genetically guided drug development, specifically addressing loss-of-function analysis, colocalization and Mendelian randomisation (MR), and the contexts in which each may be most suitable. We subsequently present a range of biomedical resources which can be used to annotate and prioritise disease-associated proteins identified by these studies including 1) ontologies to map genes, proteins, and disease, 2) resources for determining the druggability of a potential target, 3) tissue and cell expression of the gene encoding the potential target, and 4) key biological pathways involving the potential target. We illustrate these concepts through a worked example, identifying a prioritised set of plasma proteins associated with non-alcoholic fatty liver disease (NAFLD). We identified five proteins with strong genetic support for involvement with NAFLD: CYB5A, NT5C, NCAN, TGFBI and DAPK2. All of the identified proteins were expressed in both liver and adipose tissues, with TGFBI and DAPK2 being potentially druggable. In conclusion, the current review provides an overview of genetic evidence for drug target identification, and how biomedical databases can be used to provide actionable prioritisation, fully informing downstream experimental validation.

Comparing the effects of CETP in East Asian and European ancestries: a Mendelian randomization study.

CETP inhibitors are a class of lipid-lowering drugs in development for treatment of coronary heart disease (CHD). Genetic studies in East Asian ancestry have interpreted the lack of CETP signal with low-density lipoprotein cholesterol (LDL-C) and lack of drug target Mendelian randomization (MR) effect on CHD as evidence that CETP inhibitors might not be effective in East Asian participants. Capitalizing on recent increases in sample size of East Asian genetic studies, we conducted a drug target MR analysis, scaled to a standard deviation increase in high-density lipoprotein cholesterol. Despite finding evidence for possible neutral effects of lower CETP levels on LDL-C, systolic blood pressure and pulse pressure in East Asians (interaction p-values < 1.6 × 10-3), effects on cardiovascular outcomes were similarly protective in both ancestry groups. In conclusion, on-target inhibition of CETP is anticipated to decrease cardiovascular disease in individuals of both European and East Asian ancestries.

Penetrance and Prognosis of MYH7 Variant-Associated Cardiomyopathies: Results From a Dutch Multicenter Cohort Study.

BACKGROUND: MYH7 variants cause hypertrophic cardiomyopathy (HCM), noncompaction cardiomyopathy (NCCM), and dilated cardiomyopathy (DCM). Screening of relatives of patients with genetic cardiomyopathy is recommended from 10 to 12 years of age onward, irrespective of the affected gene. OBJECTIVES: This study sought to study the penetrance and prognosis of MYH7 variant-associated cardiomyopathies. METHODS: In this multicenter cohort study, penetrance and major cardiomyopathy-related events (MCEs) were assessed in carriers of (likely) pathogenic MYH7 variants by using Kaplan-Meier curves and log-rank tests. Prognostic factors were evaluated using Cox regression with time-dependent coefficients. RESULTS: In total, 581 subjects (30.1% index patients, 48.4% male, median age 37.0 years [IQR: 19.5-50.2 years]) were included. HCM was diagnosed in 226 subjects, NCCM in 70, and DCM in 55. Early penetrance and MCEs (age <12 years) were common among NCCM-associated variant carriers (21.2% and 12.0%, respectively) and DCM-associated variant carriers (15.3% and 10.0%, respectively), compared with HCM-associated variant carriers (2.9% and 2.1%, respectively). Penetrance was significantly increased in carriers of converter region variants (adjusted HR: 1.87; 95% CI: 1.15-3.04; P = 0.012) and at age ≤1 year in NCCM-associated or DCM-associated variant carriers (adjusted HR: 21.17; 95% CI: 4.81-93.20; P < 0.001) and subjects with a family history of early MCEs (adjusted HR: 2.45; 95% CI: 1.09-5.50; P = 0.030). The risk of MCE was increased in subjects with a family history of early MCEs (adjusted HR: 1.82; 95% CI: 1.15-2.87; P = 0.010) and at age ≤5 years in NCCM-associated or DCM-associated variant carriers (adjusted HR: 38.82; 95% CI: 5.16-291.88; P < 0.001). CONCLUSIONS: MYH7 variants can cause cardiomyopathies and MCEs at a young age. Screening at younger ages may be warranted, particularly in carriers of NCCM- or DCM-associated variants and/or with a family history of MCEs at <12 years.

A Machine Learning Model to Aid Detection of Familial Hypercholesterolemia.

Background: People with monogenic familial hypercholesterolemia (FH) are at an increased risk of premature coronary heart disease and death. With a prevalence of 1:250, FH is relatively common; but currently there is no population screening strategy in place and most carriers are identified late in life, delaying timely and cost-effective interventions. Objectives: The purpose of this study was to derive an algorithm to identify people with suspected monogenic FH for subsequent confirmatory genomic testing and cascade screening. Methods: A least absolute shrinkage and selection operator logistic regression model was used to identify predictors that accurately identified people with FH in 139,779 unrelated participants of the UK Biobank. Candidate predictors included information on medical and family history, anthropometric measures, blood biomarkers, and a low-density lipoprotein cholesterol (LDL-C) polygenic score (PGS). Model derivation and evaluation were performed in independent training and testing data. Results: A total of 488 FH variant carriers were identified using whole-exome sequencing of the low-density lipoprotein receptor, apolipoprotein B, apolipoprotein E, proprotein convertase subtilisin/kexin type 9 genes. A 14-variable algorithm for FH was derived, with an area under the curve of 0.77 (95% CI: 0.71-0.83), where the top 5 most important variables included triglyceride, LDL-C, apolipoprotein A1 concentrations, self-reported statin use, and LDL-C PGS. Excluding the PGS as a candidate feature resulted in a 9-variable model with a comparable area under the curve: 0.76 (95% CI: 0.71-0.82). Both multivariable models (w/wo the PGS) outperformed screening-prioritization based on LDL-C adjusted for statin use. Conclusions: Detecting individuals with FH can be improved by considering additional predictors. This would reduce the sequencing burden in a 2-stage population screening strategy for FH.

Exploring the Role of Plasma Lipids and Statin Interventions on Multiple Sclerosis Risk and Severity: A Mendelian Randomization Study.

BACKGROUND AND OBJECTIVES: There has been considerable interest in statins because of their pleiotropic effects beyond their lipid-lowering properties. Many of these pleiotropic effects are predominantly ascribed to Rho small guanosine triphosphatases (Rho GTPases) proteins. We aimed to genetically investigate the role of lipids and statin interventions on multiple sclerosis (MS) risk and severity. METHOD: We used two-sample Mendelian randomization (MR) to investigate (1) the causal role of genetically mimic both cholesterol-dependent (through low-density lipoprotein cholesterol (LDL-C) and cholesterol biosynthesis pathway) and cholesterol-independent (through Rho GTPases) effects of statins on MS risk and MS severity, (2) the causal link between lipids (high-density lipoprotein cholesterol [HDL-C] and triglycerides [TG]) levels and MS risk and severity, and (3) the reverse causation between lipid fractions and MS risk. We used summary statistics from the Global Lipids Genetics Consortium (GLGC), eQTLGen Consortium, and the International MS Genetics Consortium (IMSGC) for lipids, expression quantitative trait loci, and MS, respectively (GLGC: n = 188,577; eQTLGen: n = 31,684; IMSGC (MS risk): n = 41,505; IMSGC (MS severity): n = 7,069). RESULTS: The results of MR using the inverse-variance weighted method show that genetically predicted RAC2, a member of cholesterol-independent pathway (OR 0.86 [95% CI 0.78-0.95], p-value 3.80E-03), is implicated causally in reducing MS risk. We found no evidence for the causal role of LDL-C and the member of cholesterol biosynthesis pathway on MS risk. The MR results also show that lifelong higher HDL-C (OR 1.14 [95% CI 1.04-1.26], p-value 7.94E-03) increases MS risk but TG was not. Furthermore, we found no evidence for the causal role of lipids and genetically mimicked statins on MS severity. There is no evidence of reverse causation between MS risk and lipids. DISCUSSION: Evidence from this study suggests that RAC2 is a genetic modifier of MS risk. Because RAC2 has been reported to mediate some of the pleiotropic effects of statins, we suggest that statins may reduce MS risk through a cholesterol-independent pathway (that is, RAC2-related mechanism(s)). MR analyses also support a causal effect of HDL-C on MS risk.

Unraveling the relationships between alpha- and beta-adrenergic modulation and the risk of heart failure.

Background: The effects of α and ß adrenergic receptor modulation on the risk of developing heart failure (HF) remains uncertain due to a lack of randomized controlled trials. This study aimed to estimate the effects of α and ß adrenergic receptors modulation on the risk of HF and to provide proof of principle for genetic target validation studies in HF. Methods: Genetic variants within the cis regions encoding the adrenergic receptors α1A, α2B, ß1, and ß2 associated with blood pressure in a 757,601-participant genome-wide association study (GWAS) were selected as instruments to perform a drug target Mendelian randomization study. Effects of these variants on HF risk were derived from the HERMES GWAS (542,362 controls; 40,805 HF cases). Results: Lower α1A or ß1 activity was associated with reduced HF risk: odds ratio (OR) 0.83 (95% CI 0.74-0.93, P = 0.001) and 0.95 (95% CI 0.93-0.97, P = 8 × 10-6). Conversely, lower α2B activity was associated with increased HF risk: OR 1.09 (95% CI 1.05-1.12, P = 3 × 10-7). No evidence of an effect of lower ß2 activity on HF risk was found: OR 0.99 (95% CI 0.92-1.07, P = 0.95). Complementary analyses showed that these effects were consistent with those on left ventricular dimensions and acted independently of any potential effect on coronary artery disease. Conclusions: This study provides genetic evidence that α1A or ß1 receptor inhibition will likely decrease HF risk, while lower α2B activity may increase this risk. Genetic variant analysis can assist with drug development for HF prevention.

Biomedical consequences of elevated cholesterol-containing lipoproteins and apolipoproteins on cardiovascular and non-cardiovascular outcomes.

BACKGROUND: Higher concentrations of cholesterol-containing low-density lipoprotein (LDL-C) increase the risk of cardiovascular disease (CVD). The association of LDL-C with non-CVD traits remains unclear, as are the possible independent contributions of other cholesterol-containing lipoproteins and apolipoproteins. METHODS: Nuclear magnetic resonance spectroscopy was used to measure the cholesterol content of high density (HDL-C), very low-density (VLDL-C), intermediate-density (IDL-C), as well as low-density lipoprotein fractions, the apolipoproteins Apo-A1 and Apo-B, as well as total triglycerides (TG), remnant-cholesterol (Rem-Chol) and total cholesterol (TC). The causal effects of these exposures were assessed against 33 outcomes using univariable and multivariable Mendelian randomization (MR). RESULTS: The majority of cholesterol containing lipoproteins and apolipoproteins affect coronary heart disease (CHD), carotid intima-media thickness, carotid plaque, C-reactive protein (CRP) and blood pressure. Multivariable MR indicated that many of these effects act independently of HDL-C, LDL-C and TG, the most frequently measured lipid fractions. Higher concentrations of TG, VLDL-C, Rem-Chol and Apo-B increased heart failure (HF) risk; often independently of LDL-C, HDL-C or TG. Finally, a subset of these exposures associated with non-CVD traits such as Alzheimer's disease (AD: HDL-C, LDL-C, IDL-C, Apo-B), type 2 diabetes (T2DM: VLDL-C, IDL-C, LDL-C), and inflammatory bowel disease (IBD: LDL-C, IDL-C). CONCLUSIONS: The cholesterol content of a wide range of lipoprotein and apolipoproteins associate with measures of atherosclerosis, blood pressure, CRP, and CHD, with a subset affecting HF, T2DM, AD and IBD risk. Many of the observed effects appear to act independently of LDL-C, HDL-C, and TG, supporting the targeting of lipid fractions beyond LDL-C for disease prevention.

It is known that increases in the amount of certain fats and proteins in the blood can lead to heart attacks. These increases are also found in people with other diseases. Here, we looked at inherited differences in some fats and proteins in blood to explore whether these could be associated with various diseases. We found that some fats and proteins in blood were associated with heart disease (including heart failure), blood pressure, blockages in blood vessels, and to a lesser extent with diabetes, Alzheimer's disease, and inflammatory bowel disease. These findings suggest that changes to lipids and proteins in the blood might lead to various diseases, including some that are not normally associated with changes in the blood. Monitoring these changes could improve diagnosis and treatment of these diseases.