Agonist-independent GPCR activity regulates anterior-posterior targeting of olfactory sensory neurons.

G-protein-coupled receptors (GPCRs) are known to possess two different conformations, active and inactive, and they spontaneously alternate between the two in the absence of ligands. Here, we analyzed the agonist-independent GPCR activity for its possible role in receptor-instructed axonal projection. We generated transgenic mice expressing activity mutants of the ß2-adrenergic receptor, a well-characterized GPCR with the highest homology to odorant receptors (ORs). We found that mutants with altered agonist-independent activity changed the transcription levels of axon-targeting molecules--e.g., Neuropilin-1 and Plexin-A1--but not of glomerular segregation molecules--e.g., Kirrel2 and Kirrel3--thus causing shifts in glomerular locations along the anterior-posterior (A-P) axis. Knockout and in vitro experiments demonstrated that Gs, but not Golf, is responsible for mediating the agonist-independent GPCR activity. We conclude that the equilibrium of conformational transitions set by each OR is the major determinant of expression levels of A-P-targeting molecules.

Significance tests for R2 of out-of-sample prediction using polygenic scores.

The coefficient of determination (R2) is a well-established measure to indicate the predictive ability of polygenic scores (PGSs). However, the sampling variance of R2 is rarely considered so that 95% confidence intervals (CI) are not usually reported. Moreover, when comparisons are made between PGSs based on different discovery samples, the sampling covariance of R2 is required to test the difference between them. Here, we show how to estimate the variance and covariance of R2 values to assess the 95% CI and p value of the R2 difference. We apply this approach to real data calculating PGSs in 28,880 European participants derived from UK Biobank (UKBB) and Biobank Japan (BBJ) GWAS summary statistics for cholesterol and BMI. We quantify the significantly higher predictive ability of UKBB PGSs compared to BBJ PGSs (p value 7.6e-31 for cholesterol and 1.4e-50 for BMI). A joint model of UKBB and BBJ PGSs significantly improves the predictive ability, compared to a model of UKBB PGS only (p value 3.5e-05 for cholesterol and 1.3e-28 for BMI). We also show that the predictive ability of regulatory SNPs is significantly enriched over non-regulatory SNPs for cholesterol (p value 8.9e-26 for UKBB and 3.8e-17 for BBJ). We suggest that the proposed approach (available in R package r2redux) should be used to test the statistical significance of difference between pairs of PGSs, which may help to draw a correct conclusion about the comparative predictive ability of PGSs.

Gsα Regulates Macrophage Foam Cell Formation During Atherosclerosis.

BACKGROUND: Many cardiovascular pathologies are induced by signaling through G-protein-coupled receptors via Gsα (G protein stimulatory α subunit) proteins. However, the specific cellular mechanisms that are driven by Gsα and contribute to the development of atherosclerosis remain unclear. METHODS: High-throughput screening involving data from single-cell and bulk sequencing were used to explore the expression of Gsα in atherosclerosis. The differentially expression and activity of Gsα were analyzed by immunofluorescence and cAMP measurements. Macrophage-specific Gsα knockout (Mac-GsαKO) mice were generated to study the effect on atherosclerosis. The role of Gsα was determined by transplanting bone marrow and performing assays for foam cell formation, Dil-ox-LDL (oxidized low-density lipoprotein) uptake, chromatin immunoprecipitation, and luciferase reporter assays. RESULTS: ScRNA-seq showed elevated Gnas in atherosclerotic mouse aorta's cholesterol metabolism macrophage cluster, while bulk sequencing confirmed increased GNAS expression in human plaque macrophage content. A significant upregulation of Gsα and active Gsα occurred in macrophages from human and mouse plaques. Ox-LDL could translocate Gsα from macrophage lipid rafts in short-term and promote Gnas transcription through ERK1/2 activation and C/EBPß phosphorylation via oxidative stress in long-term. Atherosclerotic lesions from Mac-GsαKO mice displayed decreased lipid deposition compared with those from control mice. Additionally, Gsα deficiency alleviated lipid uptake and foam cell formation. Mechanistically, Gsα increased the levels of cAMP and transcriptional activity of the cAMP response element binding protein, which resulted in increased expression of CD36 and SR-A1. In the translational experiments, inhibiting Gsα activation with suramin or cpGN13 reduced lipid uptake, foam cell formation, and the progression of atherosclerotic plaques in mice in vivo. CONCLUSIONS: Gsα activation is enhanced during atherosclerotic progression and increases lipid uptake and foam cell formation. The genetic or chemical inactivation of Gsα inhibit the development of atherosclerosis in mice, suggesting that drugs targeting Gsα may be useful in the treatment of atherosclerosis.

Mitigating type 1 error inflation and power loss in GxE PRS: Genotype-environment interaction in polygenic risk score models.

The use of polygenic risk score (PRS) models has transformed the field of genetics by enabling the prediction of complex traits and diseases based on an individual's genetic profile. However, the impact of genotype-environment interaction (GxE) on the performance and applicability of PRS models remains a crucial aspect to be explored. Currently, existing genotype-environment interaction polygenic risk score (GxE PRS) models are often inappropriately used, which can result in inflated type 1 error rates and compromised results. In this study, we propose novel GxE PRS models that jointly incorporate additive and interaction genetic effects although also including an additional quadratic term for nongenetic covariates, enhancing their robustness against model misspecification. Through extensive simulations, we demonstrate that our proposed models outperform existing models in terms of controlling type 1 error rates and enhancing statistical power. Furthermore, we apply the proposed models to real data, and report significant GxE effects. Specifically, we highlight the impact of our models on both quantitative and binary traits. For quantitative traits, we uncover the GxE modulation of genetic effects on body mass index by alcohol intake frequency. In the case of binary traits, we identify the GxE modulation of genetic effects on hypertension by waist-to-hip ratio. These findings underscore the importance of employing a robust model that effectively controls type 1 error rates, thus preventing the occurrence of spurious GxE signals. To facilitate the implementation of our approach, we have developed an innovative R software package called GxEprs, specifically designed to detect and estimate GxE effects. Overall, our study highlights the importance of accurate GxE modeling and its implications for genetic risk prediction, although providing a practical tool to support further research in this area.

Genetic correlations of polygenic disease traits: from theory to practice.

The genetic correlation describes the genetic relationship between two traits and can contribute to a better understanding of the shared biological pathways and/or the causality relationships between them. The rarity of large family cohorts with recorded instances of two traits, particularly disease traits, has made it difficult to estimate genetic correlations using traditional epidemiological approaches. However, advances in genomic methodologies, such as genome-wide association studies, and widespread sharing of data now allow genetic correlations to be estimated for virtually any trait pair. Here, we review the definition, estimation, interpretation and uses of genetic correlations, with a focus on applications to human disease.

Proteome Remodeling of the Eye Lens at 50 Years Identified With Data-Independent Acquisition.

The eye lens is responsible for focusing and transmitting light to the retina. The lens does this in the absence of organelles, yet maintains transparency for at least 5 decades before onset of age-related nuclear cataract (ARNC). It is hypothesized that oxidative stress contributes significantly to ARNC formation. It is in addition hypothesized that transparency is maintained by a microcirculation system that delivers antioxidants to the lens nucleus and exports small molecule waste. Common data-dependent acquisition methods are hindered by dynamic range of lens protein expression and provide limited context to age-related changes in the lens. In this study, we utilized data-independent acquisition mass spectrometry to analyze the urea-insoluble membrane protein fractions of 16 human lenses subdivided into three spatially distinct lens regions to characterize age-related changes, particularly concerning the lens microcirculation system and oxidative stress response. In this pilot cohort, we measured 4788 distinct protein groups, 46,681 peptides, and 7592 deamidated sequences, more than in any previous human lens data-dependent acquisition approach. Principally, we demonstrate that a significant proteome remodeling event occurs at approximately 50 years of age, resulting in metabolic preference for anaerobic glycolysis established with organelle degradation, decreased abundance of protein networks involved in calcium-dependent cell-cell contacts while retaining networks related to oxidative stress response. Furthermore, we identified multiple antioxidant transporter proteins not previously detected in the human lens and describe their spatiotemporal and age-related abundance changes. Finally, we demonstrate that aquaporin-5, among other proteins, is modified with age by post-translational modifications including deamidation and truncation. We suggest that the continued accumulation of each of these age-related outcomes in proteome remodeling contribute to decreased fiber cell permeability and result in ARNC formation.

Activity and safety of enobosarm, a novel, oral, selective androgen receptor modulator, in androgen receptor-positive, oestrogen receptor-positive, and HER2-negative advanced breast cancer (Study G200802): a randomised, open-label, multicentre, multinational, parallel design, phase 2 trial.

BACKGROUND: The androgen receptor is a tumour suppressor in oestrogen receptor-positive breast cancer. The activity and safety of enobosarm, an oral selective androgen receptor modulator, was evaluated in women with oestrogen receptor (ER)-positive, HER2-negative, and androgen receptor (AR)-positive disease. METHODS: Women who were postmenopausal (aged ≥18 years) with previously treated ER-positive, HER2-negative, locally advanced or metastatic breast cancer with an Eastern Cooperative Oncology Group performance status of 0-2 were enrolled in a randomised, open-label, multicentre, multinational, parallel design, phase 2 trial done at 35 cancer treatment centres in nine countries. Participants were stratified on the setting of immediately preceding endocrine therapy and the presence of bone-only metastasis and randomly assigned (1:1) to 9 mg or 18 mg oral enobosarm daily using an interactive web response system. The primary endpoint was clinical benefit rate at 24 weeks in those with centrally confirmed AR-positive disease (ie, the evaluable population). This trial is registered with ClinicalTrials.gov (NCT02463032). FINDINGS: Between Sept 10, 2015, and Nov 28, 2017, 136 (79%) of 172 patients deemed eligible were randomly assigned to 9 mg (n=72) or 18 mg (n=64) oral enobosarm daily. Of these 136 patients, 102 (75%) patients formed the evaluable population (9 mg, n=50; 18 mg, n=52). The median age was 60·5 years (IQR 52·3-69·3) in the 9 mg group and 62·5 years (54·0-69·3) in the 18 mg group. The median follow-up was 7·5 months (IQR 2·9-14·1). At 24 weeks, 16 (32%, 95% CI 20-47) of 50 in the 9 mg group and 15 (29%, 17-43) of 52 in the 18 mg group had clinical benefit. Six (8%) of 75 patients who received 9 mg and ten (16%) of 61 patients who received 18 mg had grade 3 or grade 4 drug-related adverse events, most frequently increased hepatic transaminases (three [4%] of 75 in the 9 mg group and two [3%] of 61 in the 18 mg group), hypercalcaemia (two [3%] and two [3%]), and fatigue (one [1%] and two [3%]). Four deaths (one in the 9 mg group and three in the 18 mg group) were deemed unrelated to the study drug. INTERPRETATION: Enobosarm has anti-tumour activity in patients with ER-positive, HER2-negative advanced breast cancer, showing that AR activation can result in clinical benefit, supporting further clinical investigation of selective AR activation strategies for the treatment of AR-positive, ER-positive, HER2-negative advanced breast cancer. FUNDING: GTx.

Phenotypic variance partitioning by transcriptomic gene expression levels and environmental variables for anthropometric traits using GTEx data.

Phenotypic variation in human is the results of genetic variation and environmental influences. Understanding the contribution of genetic and environmental components to phenotypic variation is of great interest. The variance explained by genome-wide single nucleotide polymorphisms (SNPs) typically represents a small proportion of the phenotypic variance for complex traits, which may be because the genome is only a part of the whole biological process to shape the phenotypes. In this study, we propose to partition the phenotypic variance of three anthropometric traits, using gene expression levels and environmental variables from GTEx data. We use the gene expression of four tissues that are deemed relevant for the anthropometric traits (two adipose tissues, skeletal muscle tissue and blood tissue). Additionally, we estimate the transcriptome-environment correlation that partly underlies the phenotypes of the anthropometric traits. We found that genetic factors play a significant role in determining body mass index (BMI), with the proportion of phenotypic variance explained by gene expression levels of visceral adipose tissue being 0.68 (SE = 0.06). However, we also observed that environmental factors such as age, sex, ancestry, smoking status, and drinking alcohol status have a small but significant impact (0.005, SE = 0.001). Interestingly, we found a significant negative correlation between the transcriptomic and environmental effects on BMI (transcriptome-environment correlation = -0.54, SE = 0.14), suggesting an antagonistic relationship. This implies that individuals with lower genetic profiles may be more susceptible to the effects of environmental factors on BMI, while those with higher genetic profiles may be less susceptible. We also show that the estimated transcriptomic variance varies across tissues, e.g., the gene expression levels of whole blood tissue and environmental variables explain a lower proportion of BMI phenotypic variance (0.16, SE = 0.05 and 0.04, SE = 0.004 respectively). We observed a significant positive correlation between transcriptomic and environmental effects (1.21, SE = 0.23) for this tissue. In conclusion, phenotypic variance partitioning can be done using gene expression and environmental data even with a small sample size (n = 838 from GTEx data), which can provide insights into how the transcriptomic and environmental effects contribute to the phenotypes of the anthropometric traits.

R2ROC: an efficient method of comparing two or more correlated AUC from out-of-sample prediction using polygenic scores.

Polygenic risk scores (PRSs) enable early prediction of disease risk. Evaluating PRS performance for binary traits commonly relies on the area under the receiver operating characteristic curve (AUC). However, the widely used DeLong's method for comparative significance tests suffer from limitations, including computational time and the lack of a one-to-one mapping between test statistics based on AUC and R 2 . To overcome these limitations, we propose a novel approach that leverages the Delta method to derive the variance and covariance of AUC values, enabling a comprehensive and efficient comparative significance test. Our approach offers notable advantages over DeLong's method, including reduced computation time (up to 150-fold), making it suitable for large-scale analyses and ideal for integration into machine learning frameworks. Furthermore, our method allows for a direct one-to-one mapping between AUC and R 2 values for comparative significance tests, providing enhanced insights into the relationship between these measures and facilitating their interpretation. We validated our proposed approach through simulations and applied it to real data comparing PRSs for diabetes and coronary artery disease (CAD) prediction in a cohort of 28,880 European individuals. The PRSs were derived using genome-wide association study summary statistics from two distinct sources. Our approach enabled a comprehensive and informative comparison of the PRSs, shedding light on their respective predictive abilities for diabetes and CAD. This advancement contributes to the assessment of genetic risk factors and personalized disease prediction, supporting better healthcare decision-making.

Unraveling phenotypic variance in metabolic syndrome through multi-omics.

Complex multi-omics effects drive the clustering of cardiometabolic risk factors, underscoring the imperative to comprehend how individual and combined omics shape phenotypic variation. Our study partitions phenotypic variance in metabolic syndrome (MetS), blood glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and blood pressure through genome, transcriptome, metabolome, and exposome (i.e., lifestyle exposome) analyses. Our analysis included a cohort of 62,822 unrelated individuals with white British ancestry, sourced from the UK biobank. We employed linear mixed models to partition phenotypic variance using the restricted maximum likelihood (REML) method, implemented in MTG2 (v2.22). We initiated the analysis by individually modeling omics, followed by subsequent integration of pairwise omics in a joint model that also accounted for the covariance and interaction between omics layers. Finally, we estimated the correlations of various omics effects between the phenotypes using bivariate REML. Significant proportions of the MetS variance were attributed to distinct data sources: genome (9.47%), transcriptome (4.24%), metabolome (14.34%), and exposome (3.77%). The phenotypic variances explained by the genome, transcriptome, metabolome, and exposome ranged from 3.28% for GLU to 25.35% for HDL-C, 0% for GLU to 19.34% for HDL-C, 4.29% for systolic blood pressure (SBP) to 35.75% for TG, and 0.89% for GLU to 10.17% for HDL-C, respectively. Significant correlations were found between genomic and transcriptomic effects for TG and HDL-C. Furthermore, significant interaction effects between omics data were detected for both MetS and its components. Interestingly, significant correlation of omics effect between the phenotypes was found. This study underscores omics' roles, interaction effects, and random-effects covariance in unveiling phenotypic variation in multi-omics domains.

Cross-ancestry genetic architecture and prediction for cholesterol traits.

While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.

Increased risk of haematological malignancy in adults over age 60 with thrombocytopenia compared with matched controls: Time for an upfront bone marrow evaluation?

International societies have conflicting recommendations on whether bone marrow aspirate/biopsy (BMB) is needed during workup for isolated thrombocytopenia. Our objective was to determine if thrombocytopenia in patients aged ≥60 years is associated with an increased incidence of haematological malignancy. We performed a retrospective population-based cohort study in patients aged ≥60 years between January 1, 2009 to December 31, 2019. Exposed patients had specialist consultation for thrombocytopenia, with platelet count <100 × 109/L, but normal haemoglobin and white blood cell count. Unexposed patients were those who never had specialist consultation for thrombocytopenia and whose platelets were ≥100 × 109/L. The primary outcome was the diagnosis of haematological malignancy using a competing risk of death model. During 4.0 years (IQR 2.2-6.7) of follow-up, 378/4930 exposed (19.1/1000PY, 95% CI 17.1-21.0), and 204/17556 unexposed patients (2.5/1000PY, 95% CI 2.2-2.8) were diagnosed with haematological malignancy (HR 15.5 (95% CI 11.3-21.4, p < 0.0001) in year 1, and 5.3 (95% CI 4.4-6.6, p < 0.0001) in years 2+). This finding persisted in analyses stratified by sex, age, severity, or duration of thrombocytopenia, and treatment with corticosteroids within 2 weeks of consultation. This study found a strong association between isolated thrombocytopenia and haematological malignancy in patients ≥60 years, supporting consideration of diagnostic testing including BMB during outpatient specialist consultation.

Parathyroid Hormone Resistance and Autoantibodies to the PTH1 Receptor.

We describe two cases of acquired parathyroid hormone (PTH) resistance consequent to the development of serum PTH type 1 receptor (PTH1R) autoantibodies, which block PTH binding and signaling. Both cases were associated with other autoimmune manifestations, and one case was associated with atypical membranous glomerulonephritis. In vitro binding and signaling assays identified the presence of PTH1R-blocking IgG autoantibodies, which were not present in serum samples from patients with other renal or autoimmune disorders. (Funded by the Intramural Research Programs of the National Institute of Diabetes and Digestive and Kidney Diseases and others.).

Amivantamab plus chemotherapy with and without lazertinib in EGFR-mutant advanced NSCLC after disease progression on osimertinib: primary results from the phase III MARIPOSA-2 study.

BACKGROUND: Amivantamab plus carboplatin-pemetrexed (chemotherapy) with and without lazertinib demonstrated antitumor activity in patients with refractory epidermal growth factor receptor (EGFR)-mutated advanced non-small-cell lung cancer (NSCLC) in phase I studies. These combinations were evaluated in a global phase III trial. PATIENTS AND METHODS: A total of 657 patients with EGFR-mutated (exon 19 deletions or L858R) locally advanced or metastatic NSCLC after disease progression on osimertinib were randomized 2 : 2 : 1 to receive amivantamab-lazertinib-chemotherapy, chemotherapy, or amivantamab-chemotherapy. The dual primary endpoints were progression-free survival (PFS) of amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy. During the study, hematologic toxicities observed in the amivantamab-lazertinib-chemotherapy arm necessitated a regimen change to start lazertinib after carboplatin completion. RESULTS: All baseline characteristics were well balanced across the three arms, including by history of brain metastases and prior brain radiation. PFS was significantly longer for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy [hazard ratio (HR) for disease progression or death 0.48 and 0.44, respectively; P < 0.001 for both; median of 6.3 and 8.3 versus 4.2 months, respectively]. Consistent PFS results were seen by investigator assessment (HR for disease progression or death 0.41 and 0.38 for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy, respectively; P < 0.001 for both; median of 8.2 and 8.3 versus 4.2 months, respectively). Objective response rate was significantly higher for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy (64% and 63% versus 36%, respectively; P < 0.001 for both). Median intracranial PFS was 12.5 and 12.8 versus 8.3 months for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy (HR for intracranial disease progression or death 0.55 and 0.58, respectively). Predominant adverse events (AEs) in the amivantamab-containing regimens were hematologic, EGFR-, and MET-related toxicities. Amivantamab-chemotherapy had lower rates of hematologic AEs than amivantamab-lazertinib-chemotherapy. CONCLUSIONS: Amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy improved PFS and intracranial PFS versus chemotherapy in a population with limited options after disease progression on osimertinib. Longer follow-up is needed for the modified amivantamab-lazertinib-chemotherapy regimen.

Amivantamab plus lazertinib versus osimertinib in first-line EGFR-mutant advanced non-small-cell lung cancer with biomarkers of high-risk disease: a secondary analysis from MARIPOSA.

BACKGROUND: Amivantamab-lazertinib significantly prolonged progression-free survival (PFS) versus osimertinib in patients with epidermal growth factor receptor (EGFR)-mutant advanced non-small-cell lung cancer [NSCLC; hazard ratio (HR) 0.70; P < 0.001], including those with a history of brain metastases (HR 0.69). Patients with TP53 co-mutations, detectable circulating tumor DNA (ctDNA), baseline liver metastases, and those without ctDNA clearance on treatment have poor prognoses. We evaluated outcomes in these high-risk subgroups. PATIENTS AND METHODS: This analysis included patients with treatment-naive, EGFR-mutant advanced NSCLC randomized to amivantamab-lazertinib (n = 429) or osimertinib (n = 429) in MARIPOSA. Pathogenic alterations were identified by next-generation sequencing (NGS) of baseline blood ctDNA with Guardant360 CDx. Ex19del and L858R ctDNA in blood was analyzed at baseline and cycle 3 day 1 (C3D1) with Biodesix droplet digital polymerase chain reaction (ddPCR). RESULTS: Baseline ctDNA for NGS of pathogenic alterations was available for 636 patients (amivantamab-lazertinib, n = 320; osimertinib, n = 316). Amivantamab-lazertinib improved median PFS (mPFS) versus osimertinib for patients with TP53 co-mutations {18.2 versus 12.9 months; HR 0.65 [95% confidence interval (CI) 0.48-0.87]; P = 0.003} and for patients with wild-type TP53 [22.1 versus 19.9 months; HR 0.75 (95% CI 0.52-1.07)]. In patients with EGFR-mutant, ddPCR-detectable baseline ctDNA, amivantamab-lazertinib significantly prolonged mPFS versus osimertinib [20.3 versus 14.8 months; HR 0.68 (95% CI 0.53-0.86); P = 0.002]. Amivantamab-lazertinib significantly improved mPFS versus osimertinib in patients without ctDNA clearance at C3D1 [16.5 versus 9.1 months; HR 0.49 (95% CI 0.27-0.87); P = 0.015] and with clearance [24.0 versus 16.5 months; HR 0.64 (95% CI 0.48-0.87); P = 0.004]. Amivantamab-lazertinib significantly prolonged mPFS versus osimertinib among randomized patients with [18.2 versus 11.0 months; HR 0.58 (95% CI 0.37-0.91); P = 0.017] and without baseline liver metastases [24.0 versus 18.3 months; HR 0.74 (95% CI 0.60-0.91); P = 0.004]. CONCLUSIONS: Amivantamab-lazertinib effectively overcomes the effect of high-risk features and represents a promising new standard of care for patients with EGFR-mutant advanced NSCLC.

Association of hospital-treated infectious diseases and infection burden with cardiovascular diseases and life expectancy.

BACKGROUND: The association of a broad spectrum of infectious diseases with cardiovascular outcomes remains unclear. OBJECTIVES: We aim to provide the cardiovascular risk profiles associated with a wide range of infectious diseases and explore the extent to which infections reduce life expectancy. METHODS: We ascertained exposure to 900+ infectious diseases before cardiovascular disease (CVD) onset in 453,102 participants from the UK Biobank study. Time-varying Cox proportional hazard models were used. Life table was used to estimate the life expectancy of individuals aged ≥50 with different levels of infection burden (defined as the number of infection episodes over time and the number of co-occurring infections). RESULTS: Infectious diseases were associated with a greater risk of CVD events (adjusted HR [aHR] 1.79 [95% confidence interval {CI} 1.74-1.83]). For type-specific analysis, bacterial infection with sepsis had the strongest risk of CVD events [aHR 4.76 (4.35-5.20)]. For site-specific analysis, heart and circulation infections posed the greatest risk of CVD events [aHR 4.95 (95% CI 3.77-6.50)], whereas noncardiac infections also showed excess risk [1.77 (1.72-1.81)]. Synergistic interactions were observed between infections and genetic risk score. A dose-response relationship was found between infection burden and CVD risks (p-trend <0.001). Infection burden >1 led to a CVD-related life loss at age 50 by 9.3 years [95% CI 8.6-10.3]) for men and 6.6 years [5.5-7.8] for women. CONCLUSIONS: The magnitude of the infection-CVD association showed specificity in sex, pathogen type, infection burden, and infection site. High genetic risk and infection synergistically increased the CVD risk.

"I couldn't carry on taking a drug like that": A qualitative study of patient perspectives on side effects from rheumatology drugs.

OBJECTIVES: There is growing interest in collecting outcome information directly from patients in clinical trials. This study evaluates what patients with rheumatic and musculoskeletal diseases (RMDs) consider important to know about symptomatic side effects they may experience from a new prescription drug. METHODS: Patients with inflammatory arthritis, who had one or more prescribed drugs for their disease for at least 12 months, participated in focus groups and individual interviews. Discussions were analysed using reflexive thematic analysis. RESULTS: We conducted seven focus groups with 34 participants across three continents. We found four overarching and two underpinning themes. The 'impact on life' was connected to participants 'daily life', 'family life', 'work life', and 'social life'. In 'psychological and physical aspects' participants described 'limitation to physical function', 'emotional dysregulation' and 'an overall mental state'. Extra tests, hospital visits and payment for medication were considered a 'time, energy and financial burden' of side effects. Participants explained important measurement issues to be 'severity', 'frequency', and 'duration'. Underpinning these issues, participants evaluated the 'benefit-harm-balance' which includes 'the cumulative burden' of having several side effects and the persistence of side effects over time. CONCLUSIONS: In treatment for RMDs, there seems to be an urgent need for feasible measures of patient-reported bother (impact on life and cumulative burden) from side effects and the benefit-harm-balance. These findings contribute new evidence in support of a target domain-an outcome that represents the patient voice evaluating the symptomatic treatment-related side effects for people with RMDs enrolled in clinical trials.

Gut bacteriome and mood disorders in women with PCOS.

STUDY QUESTION: How does the gut bacteriome differ based on mood disorders (MDs) in women with polycystic ovary syndrome (PCOS), and how can the gut bacteriome contribute to the associations between these two conditions? SUMMARY ANSWER: Women with PCOS who also have MDs exhibited a distinct gut bacteriome with reduced alpha diversity and a significantly lower abundance of Butyricicoccus compared to women with PCOS but without MDs. WHAT IS KNOWN ALREADY: Women with PCOS have a 4- to 5-fold higher risk of having MDs compared to women without PCOS. The gut bacteriome has been suggested to influence the pathophysiology of both PCOS and MDs. STUDY DESIGN, SIZE, DURATION: This population-based cohort study was derived from the Northern Finland Birth Cohort 1966 (NFBC1966), which includes all women born in Northern Finland in 1966. Women with PCOS who donated a stool sample at age 46 years (n = 102) and two BMI-matched controls for each case (n = 205), who also responded properly to the MD criteria scales, were included. PARTICIPANTS/MATERIALS, SETTING, METHODS: A total of 102 women with PCOS and 205 age- and BMI-matched women without PCOS were included. Based on the validated MD criteria, the subjects were categorized into MD or no-MD groups, resulting in the following subgroups: PCOS no-MD (n = 84), PCOS MD (n = 18), control no-MD (n = 180), and control MD (n = 25). Clinical characteristics were assessed at age 31 years and age 46 years, and stool samples were collected from the women at age 46 years, followed by the gut bacteriome analysis using 16 s rRNA sequencing. Alpha diversity was assessed using observed features and Shannon's index, with a focus on genera, and beta diversity was characterized using principal components analysis (PCA) with Bray-Curtis Dissimilarity at the genus level. Associations between the gut bacteriome and PCOS-related clinical features were explored by Spearman's correlation coefficient. A P-value for multiple testing was adjusted with the Benjamini-Hochberg false discovery rate (FDR) method. MAIN RESULTS AND THE ROLE OF CHANCE: We observed changes in the gut bacteriome associated with MDs, irrespective of whether the women also had PCOS. Similarly, PCOS MD cases showed a lower alpha diversity (Observed feature, PCOS no-MD, median 272; PCOS MD, median 208, FDR = 0.01; Shannon, PCOS no-MD, median 5.95; PCOS MD, median 5.57, FDR = 0.01) but also a lower abundance of Butyricicoccus (log-fold changeAnalysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC)=-0.90, FDRANCOM-BC=0.04) compared to PCOS no-MD cases. In contrast, in the controls, the gut bacteriome did not differ based on MDs. Furthermore, in the PCOS group, Sutterella showed positive correlations with PCOS-related clinical parameters linked to obesity (BMI, r2=0.31, FDR = 0.01; waist circumference, r2=0.29, FDR = 0.02), glucose metabolism (fasting glucose, r2=0.46, FDR < 0.001; fasting insulin, r2=0.24, FDR = 0.05), and gut barrier integrity (zonulin, r2=0.25, FDR = 0.03). LIMITATIONS, REASONS FOR CAUTION: Although this was the first study to assess the link between the gut bacteriome and MDs in PCOS and included the largest PCOS dataset for the gut microbiome analysis, the number of subjects stratified by the presence of MDs was limited when contrasted with previous studies that focused on MDs in a non-selected population. WIDER IMPLICATIONS OF THE FINDINGS: The main finding is that gut bacteriome is associated with MDs irrespective of the PCOS status, but PCOS may also modulate further the connection between the gut bacteriome and MDs. STUDY FUNDING/COMPETING INTEREST(S): This research was funded by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement (MATER, No. 813707), the Academy of Finland (project grants 315921, 321763, 336449), the Sigrid Jusélius Foundation, Novo Nordisk Foundation (NNF21OC0070372), grant numbers PID2021-12728OB-100 (Endo-Map) and CNS2022-135999 (ROSY) funded by MCIN/AEI/10.13039/501100011033 and ERFD A Way of Making Europe. The study was also supported by EU QLG1-CT-2000-01643 (EUROBLCS) (E51560), NorFA (731, 20056, 30167), USA/NIH 2000 G DF682 (50945), the Estonian Research Council (PRG1076, PRG1414), EMBO Installation (3573), and Horizon 2020 Innovation Grant (ERIN, No. EU952516). The funders did not participate in any process of the study. We have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.

Search for Daily Modulation of MeV Dark Matter Signals with DAMIC-M.

Dark matter (DM) particles with sufficiently large cross sections may scatter as they travel through Earth's bulk. The corresponding changes in the DM flux give rise to a characteristic daily modulation signal in detectors sensitive to DM-electron interactions. Here, we report results obtained from the first underground operation of the DAMIC-M prototype detector searching for such a signal from DM with MeV-scale mass. A model-independent analysis finds no modulation in the rate of 1 e^{-} events with sidereal period, where a DM signal would appear. We then use these data to place exclusion limits on DM in the mass range [0.53,2.7] MeV/c^{2} interacting with electrons via a dark photon mediator. Taking advantage of the time-dependent signal we improve by ∼2 orders of magnitude on our previous limit obtained from the total rate of 1 e^{-} events, using the same dataset. This daily modulation search represents the current strongest limit on DM-electron scattering via ultralight mediators for DM masses around 1 MeV/c^{2}.

An Egg Intervention Improves Ponderal But Not Linear Growth Among Infants 6-12 mo of Age in Rural Bangladesh.

BACKGROUND: Animal source foods are rich in multiple nutrients. Regular egg consumption may improve infant growth in low- and middle-income countries. OBJECTIVES: To assess the impact of daily egg consumption on linear growth among 6-12-mo olds in rural Bangladesh. METHODS: We conducted a 2 × 4 factorial cluster-randomized controlled trial allocating clusters (n = 566) to treatment for enteric pathogens or placebo and a daily egg, protein supplement, isocaloric supplement, or control. All arms received nutrition education. Here, we compare the effect of the egg intervention versus control on linear growth, a prespecified aim of the trial. Infants were enrolled at 3 mo. We measured length and weight at 6 and 12 mo and visited households weekly to distribute eggs and monitor compliance. We used linear regression models to compare 12-mo mean length, weight, and z-scores for length-for-age (LAZ), weight-for-length, and weight-for-age (WAZ), and log-binomial or robust Poisson regression to compare prevalence of stunting, wasting, and underweight between arms. We used generalized estimating equations to account for clustering and adjusted models for baseline measures of outcomes. RESULTS: We enrolled 3051 infants (n = 283 clusters) across arms, with complete 6 and 12 mo anthropometry data from 1228 infants (n = 142 clusters) in the egg arm and 1109 infants (n = 141 clusters) in the control. At baseline, 18.5%, 6.0%, and 16.4% were stunted, wasted, and underweight, respectively. The intervention did not have a statistically significant effect on mean LAZ (ß: 0.05, 95% confidence interval [CI]: -0.01, 0.10) or stunting prevalence (ß: 0.98, 95% CI: 0.89, 1.13) at 12 mo. Mean weight (ß: 0.07 kg, 95% CI: 0.02, 0.11) and WAZ (ß: 0.06, 95% CI: 0.02, 0.11) were significantly higher in the egg compared with control arms. CONCLUSIONS: Provision of a daily egg for 6 mo to infants in rural Bangladesh improved ponderal but not linear growth. TRIAL REGISTRATION NUMBER: NCT03683667, https://clinicaltrials.gov/ct2/show/NCT03683667.