From target discovery to clinical drug development with human genetics.

The substantial investments in human genetics and genomics made over the past three decades were anticipated to result in many innovative therapies. Here we investigate the extent to which these expectations have been met, excluding cancer treatments. In our search, we identified 40 germline genetic observations that led directly to new targets and subsequently to novel approved therapies for 36 rare and 4 common conditions. The median time between genetic target discovery and drug approval was 25 years. Most of the genetically driven therapies for rare diseases compensate for disease-causing loss-of-function mutations. The therapies approved for common conditions are all inhibitors designed to pharmacologically mimic the natural, disease-protective effects of rare loss-of-function variants. Large biobank-based genetic studies have the power to identify and validate a large number of new drug targets. Genetics can also assist in the clinical development phase of drugs-for example, by selecting individuals who are most likely to respond to investigational therapies. This approach to drug development requires investments into large, diverse cohorts of deeply phenotyped individuals with appropriate consent for genetically assisted trials. A robust framework that facilitates responsible, sustainable benefit sharing will be required to capture the full potential of human genetics and genomics and bring effective and safe innovative therapies to patients quickly.

Genetically Enriched Clinical Trials for Precision Development of Noncancer Therapeutics: A Scoping Review.

Genetically driven clinical trial enrichment has been proposed to accelerate and reduce the cost of developing new therapeutics. Usage of this approach has not been comprehensively reviewed. We searched Ovid MEDLINE, Embase, Web of Science, Cochrane Library, ClinicalTrials.gov, and WHO ICTRP for articles published between 2010 and 2023. Excluding absorption, distribution, metabolism, and elimination pharmacogenetic studies and anti-infectives, we found 95 completed, 4 terminated, and 22 ongoing prospective genetically enriched trials on 110 drugs for 48 nononcology, nonrare syndromic indications. Trial sizes ranged from 4 to 6,147 participants (median 72) and covered numerous disease areas, particularly neurology (30), metabolism (22), and psychiatry (17). Fifty-six completed studies (60%) met their primary end point. Overall, this scoping review demonstrates that genetically enriched trials are feasible and scalable across disease areas and provide critical information for further development, or attrition, of investigational drugs. Large, appropriately designed disease-, hospital-, or population-based biobanks will undoubtedly facilitate this type of precision drug development approach.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test.

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

Pharmacogenetics-guided dalcetrapib therapy after an acute coronary syndrome: the dal-GenE trial.

AIMS: In a retrospective analysis of dal-Outcomes, the effect of dalcetrapib on cardiovascular events was influenced by an adenylate cyclase type 9 (ADCY9) gene polymorphism. The dal-GenE study was conducted to test this pharmacogenetic hypothesis. METHODS AND RESULTS: dal-GenE was a double-blind trial in patients with an acute coronary syndrome within 1-3 months and the AA genotype at variant rs1967309 in the ADCY9 gene. A total of 6147 patients were randomly assigned to receive dalcetrapib 600 mg or placebo daily. The primary endpoint was the time from randomization to first occurrence of cardiovascular death, resuscitated cardiac arrest, non-fatal myocardial infarction, or non-fatal stroke. After a median follow-up of 39.9 months, the primary endpoint occurred in 292 (9.5%) of 3071 patients in the dalcetrapib group and 327 (10.6%) of 3076 patients in the placebo group [hazard ratio 0.88; 95% confidence interval (CI) 0.75-1.03; P = 0.12]. The hazard ratios for the components of the primary endpoint were 0.79 (95% CI 0.65-0.96) for myocardial infarction, 0.92 (95% CI 0.64-1.33) for stroke, 1.21 (95% CI 0.91-1.60) for death from cardiovascular causes, and 2.33 (95% CI 0.60-9.02) for resuscitated cardiac arrest. In a pre-specified on-treatment sensitivity analysis, the primary endpoint event rate was 7.8% (236/3015) in the dalcetrapib group and 9.3% (282/3031) in the placebo group (hazard ratio 0.83; 95% CI 0.70-0.98). CONCLUSION: Dalcetrapib did not significantly reduce the risk of occurrence of the primary endpoint of ischaemic cardiovascular events at end of study. A new trial would be needed to test the pharmacogenetic hypothesis that dalcetrapib improves the prognosis of patients with the AA genotype. CLINICAL TRIAL REGISTRATION: Trial registration dal-GenE ClinicalTrials.gov Identifier: NCT02525939.

Vitamin D and COVID-19 susceptibility and severity in the COVID-19 Host Genetics Initiative: A Mendelian randomization study.

BACKGROUND: Increased vitamin D levels, as reflected by 25-hydroxy vitamin D (25OHD) measurements, have been proposed to protect against COVID-19 based on in vitro, observational, and ecological studies. However, vitamin D levels are associated with many confounding variables, and thus associations described to date may not be causal. Vitamin D Mendelian randomization (MR) studies have provided results that are concordant with large-scale vitamin D randomized trials. Here, we used 2-sample MR to assess evidence supporting a causal effect of circulating 25OHD levels on COVID-19 susceptibility and severity. METHODS AND FINDINGS: Genetic variants strongly associated with 25OHD levels in a genome-wide association study (GWAS) of 443,734 participants of European ancestry (including 401,460 from the UK Biobank) were used as instrumental variables. GWASs of COVID-19 susceptibility, hospitalization, and severe disease from the COVID-19 Host Genetics Initiative were used as outcome GWASs. These included up to 14,134 individuals with COVID-19, and up to 1,284,876 without COVID-19, from up to 11 countries. SARS-CoV-2 positivity was determined by laboratory testing or medical chart review. Population controls without COVID-19 were also included in the control groups for all outcomes, including hospitalization and severe disease. Analyses were restricted to individuals of European descent when possible. Using inverse-weighted MR, genetically increased 25OHD levels by 1 standard deviation on the logarithmic scale had no significant association with COVID-19 susceptibility (odds ratio [OR] = 0.95; 95% CI 0.84, 1.08; p = 0.44), hospitalization (OR = 1.09; 95% CI: 0.89, 1.33; p = 0.41), and severe disease (OR = 0.97; 95% CI: 0.77, 1.22; p = 0.77). We used an additional 6 meta-analytic methods, as well as conducting sensitivity analyses after removal of variants at risk of horizontal pleiotropy, and obtained similar results. These results may be limited by weak instrument bias in some analyses. Further, our results do not apply to individuals with vitamin D deficiency. CONCLUSIONS: In this 2-sample MR study, we did not observe evidence to support an association between 25OHD levels and COVID-19 susceptibility, severity, or hospitalization. Hence, vitamin D supplementation as a means of protecting against worsened COVID-19 outcomes is not supported by genetic evidence. Other therapeutic or preventative avenues should be given higher priority for COVID-19 randomized controlled trials.

The undiagnosed disease burden associated with alpha-1 antitrypsin deficiency genotypes.

Alpha-1 antitrypsin deficiency (AATD), mainly due to the PI*ZZ genotype in SERPINA1, is one of the most common inherited diseases. Since it is associated with a high disease burden and partially prevented by smoking cessation, identification of PI*ZZ individuals through genotyping could improve health outcomes.We examined the frequency of the PI*ZZ genotype in individuals with and without diagnosed AATD from UK Biobank, and assessed the associations of the genotypes with clinical outcomes and mortality. A phenome-wide association study (PheWAS) was conducted to reveal disease associations with genotypes. A polygenic risk score (PRS) for forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio was used to evaluate variable penetrance of PI*ZZ.Among 458 164 European-ancestry participants in UK Biobank, 140 had the PI*ZZ genotype and only nine (6.4%, 95% CI 3.4-11.7%) of them were diagnosed with AATD. Those with PI*ZZ had a substantially higher odds of COPD (OR 8.8, 95% CI 5.8-13.3), asthma (OR 2.0, 95% CI 1.4-3.0), bronchiectasis (OR 7.3, 95%CI 3.2-16.8), pneumonia (OR 2.7, 95% CI 1.5-4.9) and cirrhosis (OR 7.8, 95% CI 2.5-24.6) diagnoses and a higher hazard of mortality (2.4, 95% CI 1.2-4.6), compared to PI*MM (wildtype) (n=398 424). These associations were stronger among smokers. PheWAS demonstrated associations with increased odds of empyema, pneumothorax, cachexia, polycythaemia, aneurysm and pancreatitis. Polygenic risk score and PI*ZZ were independently associated with FEV1/FVC <0.7 (OR 1.4 per 1-sd change, 95% CI 1.4-1.5 and OR 4.5, 95% CI 3.0-6.9, respectively).The important underdiagnosis of AATD, whose outcomes are partially preventable through smoking cession, could be improved through genotype-guided diagnosis.

Study design of Dal-GenE, a pharmacogenetic trial targeting reduction of cardiovascular events with dalcetrapib.

The objectives of precision medicine are to better match patient characteristics with the therapeutic intervention to optimize the chances of beneficial actions while reducing the exposure to unneeded adverse drug experiences. In a retrospective genome-wide association study of the overall neutral placebo-controlled dal-Outcomes trial, the effect of the cholesteryl ester transfer protein (CETP) modulator dalcetrapib on the composite of cardiovascular death, myocardial infarction or stroke was found to be influenced by a polymorphism in the adenylate cyclase type 9 (ADCY9) gene. Whereas patients with the AA genotype at position rs1967309 experienced fewer cardiovascular events with dalcetrapib, those with the GG genotype had an increased rate and the heterozygous AG genotype exhibited no difference from placebo. Measurements of cholesterol efflux and C-reactive protein (CRP) offered directionally supportive genotype-specific findings. In a separate, smaller, placebo-controlled trial, regression of ultrasonography-determined carotid intimal-medial thickness was only observed in dalcetrapib-treated patients with the AA genotype. Collectively, these observations led to the hypothesis that the cardiovascular effects of dalcetrapib may be pharmacogenetically determined, with a favorable benefit-risk ratio only for patients with this specific genotype. We describe below the design of dal-GenE, a precision medicine, placebo-controlled clinical outcome trial of dalcetrapib in patients with a recent acute myocardial infarction with the unique feature of selecting only those with the AA genotype at rs1967309 in the ADCY9 gene.

Genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links.

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on (1)H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10(-8)) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10(-44)) and lysine (rs8101881, P = 1.2×10(-33)), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.

[Precision medicine : a required approach for the general internist]. / Médecine de précision : un rendez-vous à ne pas manquer pour l'interniste généraliste.

The general internist cannot be a passive bystander of the anticipated medical revolution induced by precision medicine. This latter aims to improve the predictive and/or clinical course of an individual by integrating all biological, genetic, environmental, phenotypic and psychosocial knowledge of a person. In this article, national and international initiatives in the field of precision medicine are discussed as well as the potential financial, ethical and limitations of personalized medicine. The question is not to know if precision medicine will be part of everyday life but rather to integrate early the general internist in multidisciplinary teams to ensure optimal information and shared-decision process with patients and individuals.

L'interniste généraliste ne peut pas être un spectateur passif du bouleversement induit par la médecine de précision. Cette dernière vise à améliorer les aspects prédictifs ou l'évolution clinique d'une personne en intégrant toutes les connaissances biologiques et génétiques, environnementales, phénotypiques et psychosociales qui lui sont propres. Dans cet article, les initiatives nationales et internationales dans ce domaine sont abordées, ainsi que les potentiels enjeux financiers, éthiques et d'équité sociale. Cette médecine de précision fera partie de notre quotidien et il s'agit d'intégrer très tôt l'interniste généraliste dans des plateformes multidisciplinaires pour assurer les restitutions d'informations, les partages de décision, les incertitudes et ultimement contribuer au maintien de la santé de la population et améliorer la qualité des soins pour nos patients.

Low birth weight leads to obesity, diabetes and increased leptin levels in adults: the CoLaus study.

BACKGROUND: Low birth weight is associated with increased rates of obesity, insulin resistance and type 2 diabetes, but the precise mechanisms for this association remain unclear. We aimed to assess the relationships between birth weight and markers of glucose homeostasis or obesity in adults. METHODS: Cross-sectional population-based study on 1458 women and 1088 men aged 35-75 years living in Lausanne, Switzerland. Birth weight was self-reported and categorized into ≤ 2.5, 2.6-3.5, 3.6-4.0 and >4.0 kg. Body composition was assessed by bioimpedance. Leptin and adiponectin levels were measured by ELISA. RESULTS: Women with low birth weight (≤ 2.5 kg) had higher levels of fasting plasma glucose, insulin, HOMA, diabetes and metabolic syndrome; a non significant similar trend was seen in men. In both genders, height increased with birth weight, whereas a U-shaped association was found between birth weight and body mass index, waist circumference and body fat percentage. After adjusting for age, smoking status, physical activity and fat mass, an inverse association was found between leptin and birth weight categories: adjusted mean ± standard error 17.3 ± 0.7, 16.2 ± 0.3, 15.6 ± 0.5 and 14.0 ± 0.8 ng/dL for birth weight categories ≤ 2.5, 2.6-3.5, 3.6-4.0 and >4.0 kg, respectively, in women (p < 0.05) and 9.8 ± 0.8, 9.1 ± 03, 7.8 ± 0.4 and 7.7 ± 0.5 ng/dL in men (p < 0.05). An inverse association was also found between reported birth weight and leptin to fat mass ratio: mean ± standard error 0.77 ± 0.04, 0.73 ± 0.02, 0.69 ± 0.03 and 0.62 ± 0.04 in women (p < 0.05); 0.46 ± 0.05, 0.45 ± 0.02, 0.39 ± 0.02 and 0.38 ± 0.03 in men (p < 0.05). No differences in adiponectin levels were found between birth weight groups. CONCLUSIONS: Middle-aged adults born with a low weight present a higher prevalence of diabetes and obesity and also higher leptin levels and leptin to fat mass ratio than adults born with a normal weight. The higher leptin levels and leptin to fat mass ratio among adults born with a low weight might be related to nutritional factors during childhood or to the development of leptin resistance and/or higher leptin production by body fat unit. Subjects born with a low weight should be counselled regarding the risks of developing diabetes and/or cardiovascular disease.

[Genomic medicine : the challenges of information in clinical practice]. / Médecine génomique : les enjeux de l'information en pratique clinique.

The genomic revolution lifts up several potential opportunities in predictive and preventive medicine. Yet, genomic medicine opportunities can lead to clinical utility only if challenges that come with it are understood, anticipated, and faced. This review discusses the challenges that genomic medicine raises for the patients and their physicians, the general population, study participants and investigators. The article presents a program of genomic consultation in general internal medicine in the French-speaking part of Switzerland (MedOmics) that aims to address these challenges in order to optimize the clinical opportunities offered by genomic medicine.

La révolution génomique offre de nouvelles opportunités en médecine prédictive et préventive. Les opportunités liées à la médecine génomique ne connaîtront une utilité clinique que si les enjeux qui l'accompagnent sont bien compris, anticipés et relevés. Cet article discute les défis que représente la génomique pour les patients et leurs médecins, la population générale ainsi que pour les participants aux études et leurs investigateurs. L'article présente un programme de consultation romande de génomique en médecine interne générale (MedOmics) visant à répondre aux nombreux défis afin d'optimiser les opportunités cliniques offertes par la médecine génomique.

Prepublication data sharing.

Rapid release of prepublication data has served the field of genomics well. Attendees at a workshop in Toronto recommend extending the practice to other biological data sets.

Six novel susceptibility Loci for early-onset androgenetic alopecia and their unexpected association with common diseases.

Androgenetic alopecia (AGA) is a highly heritable condition and the most common form of hair loss in humans. Susceptibility loci have been described on the X chromosome and chromosome 20, but these loci explain a minority of its heritable variance. We conducted a large-scale meta-analysis of seven genome-wide association studies for early-onset AGA in 12,806 individuals of European ancestry. While replicating the two AGA loci on the X chromosome and chromosome 20, six novel susceptibility loci reached genome-wide significance (p = 2.62×10⁻9-1.01×10⁻¹²). Unexpectedly, we identified a risk allele at 17q21.31 that was recently associated with Parkinson's disease (PD) at a genome-wide significant level. We then tested the association between early-onset AGA and the risk of PD in a cross-sectional analysis of 568 PD cases and 7,664 controls. Early-onset AGA cases had significantly increased odds of subsequent PD (OR = 1.28, 95% confidence interval: 1.06-1.55, p = 8.9×10⁻³). Further, the AGA susceptibility alleles at the 17q21.31 locus are on the H1 haplotype, which is under negative selection in Europeans and has been linked to decreased fertility. Combining the risk alleles of six novel and two established susceptibility loci, we created a genotype risk score and tested its association with AGA in an additional sample. Individuals in the highest risk quartile of a genotype score had an approximately six-fold increased risk of early-onset AGA [odds ratio (OR) = 5.78, p = 1.4×10⁻88]. Our results highlight unexpected associations between early-onset AGA, Parkinson's disease, and decreased fertility, providing important insights into the pathophysiology of these conditions.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Caffeine intake and CYP1A2 variants associated with high caffeine intake protect non-smokers from hypertension.

The 15q24.1 locus, including CYP1A2, is associated with blood pressure (BP). The CYP1A2 rs762551 C allele is associated with lower CYP1A2 enzyme activity. CYP1A2 metabolizes caffeine and is induced by smoking. The association of caffeine consumption with hypertension remains controversial. We explored the effects of CYP1A2 variants and CYP1A2 enzyme activity on BP, focusing on caffeine as the potential mediator of CYP1A2 effects. Four observational (n = 16 719) and one quasi-experimental studies (n = 106) including European adults were conducted. Outcome measures were BP, caffeine intake, CYP1A2 activity and polymorphisms rs762551, rs1133323 and rs1378942. CYP1A2 variants were associated with hypertension in non-smokers, but not in smokers (CYP1A2-smoking interaction P = 0.01). Odds ratios (95% CIs) for hypertension for rs762551 CC, CA and AA genotypes were 1 (reference), 0.78 (0.59-1.02) and 0.66 (0.50-0.86), respectively, P = 0.004. Results were similar for the other variants. Higher CYP1A2 activity was linearly associated with lower BP after quitting smoking (P = 0.049 and P = 0.02 for systolic and diastolic BP, respectively), but not while smoking. In non-smokers, the CYP1A2 variants were associated with higher reported caffeine intake, which in turn was associated with lower odds of hypertension and lower BP (P = 0.01). In Mendelian randomization analyses using rs1133323 as instrument, each cup of caffeinated beverage was negatively associated with systolic BP [-9.57 (-16.22, -2.91) mmHg]. The associations of CYP1A2 variants with BP were modified by reported caffeine intake. These observational and quasi-experimental results strongly support a causal role of CYP1A2 in BP control via caffeine intake.

A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.

Whole genome sequencing (WGS) at high-depth (30X) allows the accurate discovery of variants in the coding and non-coding DNA regions and helps elucidate the genetic underpinnings of human health and diseases. Yet, due to the prohibitive cost of high-depth WGS, most large-scale genetic association studies use genotyping arrays or high-depth whole exome sequencing (WES). Here we propose a cost-effective method which we call "Whole Exome Genome Sequencing" (WEGS), that combines low-depth WGS and high-depth WES with up to 8 samples pooled and sequenced simultaneously (multiplexed). We experimentally assess the performance of WEGS with four different depth of coverage and sample multiplexing configurations. We show that the optimal WEGS configurations are 1.7-2.0 times cheaper than standard WES (no-plexing), 1.8-2.1 times cheaper than high-depth WGS, reach similar recall and precision rates in detecting coding variants as WES, and capture more population-specific variants in the rest of the genome that are difficult to recover when using genotype imputation methods. We apply WEGS to 862 patients with peripheral artery disease and show that it directly assesses more known disease-associated variants than a typical genotyping array and thousands of non-imputable variants per disease-associated locus.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.

A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Genome-wide association study identifies two loci strongly affecting transferrin glycosylation.

Polysaccharide sidechains attached to proteins play important roles in cell-cell and receptor-ligand interactions. Variation in the carbohydrate component has been extensively studied for the iron transport protein transferrin, because serum levels of the transferrin isoforms asialotransferrin + disialotransferrin (carbohydrate-deficient transferrin, CDT) are used as biomarkers of excessive alcohol intake. We conducted a genome-wide association study to assess whether genetic factors affect CDT concentration in serum. CDT was measured in three population-based studies: one in Switzerland (CoLaus study, n = 5181) and two in Australia (n = 1509, n = 775). The first cohort was used as the discovery panel and the latter ones served as replication. Genome-wide single-nucleotide polymorphism (SNP) typing data were used to identify loci with significant associations with CDT as a percentage of total transferrin (CDT%). The top three SNPs in the discovery panel (rs2749097 near PGM1 on chromosome 1, and missense polymorphisms rs1049296, rs1799899 in TF on chromosome 3) were successfully replicated , yielding genome-wide significant combined association with CDT% (P = 1.9 × 10(-9), 4 × 10(-39), 5.5 × 10(-43), respectively) and explain 5.8% of the variation in CDT%. These allelic effects are postulated to be caused by variation in availability of glucose-1-phosphate as a precursor of the glycan (PGM1), and variation in transferrin (TF) structure.

Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study.

BACKGROUND: High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal. METHODS: We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20,913 myocardial infarction cases, 95,407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12,482 cases of myocardial infarction and 41,331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol. FINDINGS: Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10(-13)) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84-0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88-1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58-0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68-1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45-1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69-2·69, p=2×10(-10)). INTERPRETATION: Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction. FUNDING: US National Institutes of Health, The Wellcome Trust, European Union, British Heart Foundation, and the German Federal Ministry of Education and Research.