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It remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, nmax = 40,914) and DIAGRAM (nmax = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (rgenetic = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.

Beta‐blockers are widely used medications for a variety of indications, including heart failure, myocardial infarction, cardiac arrhythmias, and hypertension. Genetic variability in pharmacokinetic (e.g., CYP2D6) and pharmacodynamic (e.g., ADRB1, ADRB2, ADRA2C, GRK4, GRK5) genes have been studied in relation to beta‐blocker exposure and response. We searched and summarized the strength of the evidence linking beta‐blocker exposure and response with the six genes listed above. The level of evidence was high for associations between CYP2D6 genetic variation and both metoprolol exposure and heart rate response. Evidence indicates that CYP2D6 poor metabolizers experience clinically significant greater exposure and lower heart rate in response to metoprolol compared with those who are not poor metabolizers. Therefore, we provide therapeutic recommendations regarding genetically predicted CYP2D6 metabolizer status and metoprolol therapy. However, there was insufficient evidence to make therapeutic recommendations for CYP2D6 and other beta‐blockers or for any beta‐blocker and the other five genes evaluated (updates at www.cpicpgx.org). [ABSTRACT FROM AUTHOR]

Objectives Phenotyping is a core task in observational health research utilizing electronic health records (EHRs). Developing an accurate algorithm demands substantial input from domain experts, involving extensive literature review and evidence synthesis. This burdensome process limits scalability and delays knowledge discovery. We investigate the potential for leveraging large language models (LLMs) to enhance the efficiency of EHR phenotyping by generating high-quality algorithm drafts. Materials and Methods We prompted four LLMs—GPT-4 and GPT-3.5 of ChatGPT, Claude 2, and Bard—in October 2023, asking them to generate executable phenotyping algorithms in the form of SQL queries adhering to a common data model (CDM) for three phenotypes (ie, type 2 diabetes mellitus, dementia, and hypothyroidism). Three phenotyping experts evaluated the returned algorithms across several critical metrics. We further implemented the top-rated algorithms and compared them against clinician-validated phenotyping algorithms from the Electronic Medical Records and Genomics (eMERGE) network. Results GPT-4 and GPT-3.5 exhibited significantly higher overall expert evaluation scores in instruction following, algorithmic logic, and SQL executability, when compared to Claude 2 and Bard. Although GPT-4 and GPT-3.5 effectively identified relevant clinical concepts, they exhibited immature capability in organizing phenotyping criteria with the proper logic, leading to phenotyping algorithms that were either excessively restrictive (with low recall) or overly broad (with low positive predictive values). Conclusion GPT versions 3.5 and 4 are capable of drafting phenotyping algorithms by identifying relevant clinical criteria aligned with a CDM. However, expertise in informatics and clinical experience is still required to assess and further refine generated algorithms. [ABSTRACT FROM AUTHOR]

BackgroundCoronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown.MethodsWe performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus.ResultsThe meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35-1.86; P=2.6×10-10). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14-2.57; P=0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17-2.24; P=0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18-4.75; P=0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes.ConclusionsGenetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.

We hypothesized that generalized linear mixed models (GLMMs), which estimate the additive genetic variance underlying phenotype variability, would facilitate rapid characterization of clinical phenotypes from an electronic health record. We evaluated 1,288 phenotypes in 29,349 subjects of European ancestry with single-nucleotide polymorphism (SNP) genotyping on the Illumina Exome Beadchip. We show that genetic liability estimates are primarily driven by SNPs identified by prior genome-wide association studies and SNPs within the human leukocyte antigen (HLA) region. We identify 44 (false discovery rate q

This cohort study uses patient data from the Medicaid and Children's Health Insurance Program to investigate if antipsychotic treatment of children and young adults without severe somatic illness or psychosis is associated with increased risk of death. Key Points: Question: Is antipsychotic treatment of children and young adults without severe somatic illness or psychosis associated with increased risk of death? Findings: In a cohort of 2 067 507 Medicaid patients aged 5 to 24 years, antipsychotic treatment was associated with increased risk of death only for patients with doses greater than 100-mg chlorpromazine equivalents. Risk was not significantly associated with lower doses or with either dose in children aged 5 to 17 years. Meaning: Antipsychotic treatment of 100-mg chlorpromazine equivalents or less or in children was not associated with increased mortality; further research is needed to better understand the increased risk of death with higher doses in young adults. Importance: Dose-related effects of antipsychotic medications may increase mortality in children and young adults. Objective: To compare mortality for patients aged 5 to 24 years beginning treatment with antipsychotic vs control psychiatric medications. Design, Setting, and Participants: This was a US national retrospective cohort study of Medicaid patients with no severe somatic illness or schizophrenia or related psychoses who initiated study medication treatment. Study data were analyzed from November 2022 to September 2023. Exposures: Current use of second-generation antipsychotic agents in daily doses of less than or equal to 100-mg chlorpromazine equivalents or greater than 100-mg chlorpromazine equivalents vs that for control medications (α agonists, atomoxetine, antidepressants, and mood stabilizers). Main Outcome and Measures: Total mortality, classified by underlying cause of death. Rate differences (RDs) and hazard ratios (HRs) adjusted for potential confounders with propensity score–based overlap weights. Results: The 2 067 507 patients (mean [SD] age, 13.1 [5.3] years; 1 060 194 male [51.3%]) beginning study medication treatment filled 21 749 825 prescriptions during follow-up with 5 415 054 for antipsychotic doses of 100 mg or less, 2 813 796 for doses greater than 100 mg, and 13 520 975 for control medications. Mortality was not associated with antipsychotic doses of 100 mg or less (RD, 3.3; 95% CI, −5.1 to 11.7 per 100 000 person-years; HR, 1.08; 95% CI, 0.89-1.32) but was associated with doses greater than 100 mg (RD, 22.4; 95% CI, 6.6-38.2; HR, 1.37; 95% CI, 1.11-1.70). For higher doses, antipsychotic treatment was significantly associated with overdose deaths (RD, 8.3; 95% CI, 0-16.6; HR, 1.57; 95% CI, 1.02-2.42) and other unintentional injury deaths (RD, 12.3; 95% CI, 2.4-22.2; HR, 1.57; 95% CI, 1.12-2.22) but was not associated with nonoverdose suicide deaths or cardiovascular/metabolic deaths. Mortality for children aged 5 to 17 years was not significantly associated with either antipsychotic dose, whereas young adults aged 18 to 24 years had increased risk for doses greater than 100 mg (RD, 127.5; 95% CI, 44.8-210.2; HR, 1.68; 95% CI, 1.23-2.29). Conclusions and Relevance: In this cohort study of more than 2 million children and young adults without severe somatic disease or diagnosed psychosis, antipsychotic treatment in doses of 100 mg or less of chlorpromazine equivalents or in children aged 5 to 17 years was not associated with increased risk of death. For doses greater than 100 mg, young adults aged 18 to 24 years had significantly increased risk of death, with 127.5 additional deaths per 100 000 person-years. [ABSTRACT FROM AUTHOR]

Background Benzodiazepine hypnotics and the related nonbenzodiazepine hypnotics (z-drugs) are among the most frequently prescribed medications for older adults. Both can depress respiration, which could have fatal cardiorespiratory effects, particularly among patients with concurrent opioid use. Trazodone, frequently prescribed in low doses for insomnia, has minimal respiratory effects, and, consequently, may be a safer hypnotic for older patients. Thus, for patients beginning treatment with benzodiazepine hypnotics or z-drugs, we compared deaths during periods of current hypnotic use, without or with concurrent opioids, to those for comparable patients receiving trazodone in doses up to 100 mg. Methods and findings The retrospective cohort study in the United States included 400,924 Medicare beneficiaries 65 years of age or older without severe illness or evidence of substance use disorder initiating study hypnotic therapy from January 2014 through September 2015. Study endpoints were out-of-hospital (primary) and total mortality. Hazard ratios (HRs) were adjusted for demographic characteristics, psychiatric and neurologic disorders, cardiovascular and renal conditions, respiratory diseases, pain-related diagnoses and medications, measures of frailty, and medical care utilization in a time-dependent propensity score-stratified analysis. Patients without concurrent opioids had 32,388 person-years of current use, 260 (8.0/1,000 person-years) out-of-hospital and 418 (12.9/1,000) total deaths for benzodiazepines; 26,497 person-years,150 (5.7/1,000) out-of-hospital and 227 (8.6/1,000) total deaths for z-drugs; and 16,177 person-years,156 (9.6/1,000) out-of-hospital and 256 (15.8/1,000) total deaths for trazodone. Out-of-hospital and total mortality for benzodiazepines (respective HRs: 0.99 [95% confidence interval, 0.81 to 1.22, p = 0.954] and 0.95 [0.82 to 1.14, p = 0.513] and z-drugs (HRs: 0.96 [0.76 to 1.23], p = 0.767 and 0.87 [0.72 to 1.05], p = 0.153) did not differ significantly from that for trazodone. Patients with concurrent opioids had 4,278 person-years of current use, 90 (21.0/1,000) out-of-hospital and 127 (29.7/1,000) total deaths for benzodiazepines; 3,541 person-years, 40 (11.3/1,000) out-of-hospital and 64 (18.1/1,000) total deaths for z-drugs; and 2,347 person-years, 19 (8.1/1,000) out-of-hospital and 36 (15.3/1,000) total deaths for trazodone. Out-of-hospital and total mortality for benzodiazepines (HRs: 3.02 [1.83 to 4.97], p < 0.001 and 2.21 [1.52 to 3.20], p < 0.001) and z-drugs (HRs: 1.98 [1.14 to 3.44], p = 0.015 and 1.65 [1.09 to 2.49], p = 0.018) were significantly increased relative to trazodone; findings were similar with exclusion of overdose deaths or restriction to those with cardiovascular causes. Limitations included composition of the study cohort and potential confounding by unmeasured variables. Conclusions In US Medicare beneficiaries 65 years of age or older without concurrent opioids who initiated treatment with benzodiazepine hypnotics, z-drugs, or low-dose trazodone, study hypnotics were not associated with mortality. With concurrent opioids, benzodiazepines and z-drugs were associated with increased out-of-hospital and total mortality. These findings indicate that the dangers of benzodiazepine-opioid coadministration go beyond the documented association with overdose death and suggest that in combination with opioids, the z-drugs may be more hazardous than previously thought., Author(s): Wayne A. Ray 1,*, Cecilia P. Chung 2, Katherine T. Murray 3, Beth A. Malow 4, James R. Daugherty 1, C. Michael Stein 3 Introduction Hypnotics are among the [...]