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GDNF receptor alpha-like is a brainstem-restricted receptor for growth and differentiation factor 15, regulating appetite and body weight in non-homeostatic conditions by activating the emergency circuit response to disease and toxin stresses. Brainstem receptor regulates body mass loss Growth and differentiation factor 15 (GDF15) acts on feeding centres in the brain to cause anorexia, leading to loss of both lean and fat mass and eventually cachexia. GDF15 levels rise in response to tissue stress and injury, and higher levels are associated with weight loss in numerous chronic human diseases, including cancer. Bernard Allan and colleagues now show that glial cell-derived neurotrophic factor (GDNF) receptor alpha-like (GFRAL) is a GDF15 receptor in the brainstem. The structure of GDF15 and its interaction with GFRAL together with biochemical experiments and analysis of Gfral knockout mice demonstrate that regulation of body weight by GFRAL is independent of previously characterized pathways. Unlike hormones from gut and adipose tissue that activate receptors mostly in the hypothalamus, GDF15 increases in response to tissue damage and activates GFRAL-expressing neurons in the brainstem. Gfral knockout mice overate under stressed conditions and were resistant to chemotherapy-induced anorexia and weight loss. These findings provide therapeutic opportunities for disorders with altered energy demands. Under homeostatic conditions, animals use well-defined hypothalamic neural circuits to help maintain stable body weight, by integrating metabolic and hormonal signals from the periphery to balance food consumption and energy expenditure 1 , 2 . In stressed or disease conditions, however, animals use alternative neuronal pathways to adapt to the metabolic challenges of altered energy demand 3 . Recent studies have identified brain areas outside the hypothalamus that are activated under these ‘non-homeostatic’ conditions 4 , 5 , 6 , but the molecular nature of the peripheral signals and brain-localized receptors that activate these circuits remains elusive. Here we identify glial cell-derived neurotrophic factor (GDNF) receptor alpha-like (GFRAL) as a brainstem-restricted receptor for growth and differentiation factor 15 (GDF15). GDF15 regulates food intake, energy expenditure and body weight in response to metabolic and toxin-induced stresses; we show that Gfral knockout mice are hyperphagic under stressed conditions and are resistant to chemotherapy-induced anorexia and body weight loss. GDF15 activates GFRAL-expressing neurons localized exclusively in the area postrema and nucleus tractus solitarius of the mouse brainstem. It then triggers the activation of neurons localized within the parabrachial nucleus and central amygdala, which constitute part of the ‘emergency circuit’ that shapes feeding responses to stressful conditions 7 . GDF15 levels increase in response to tissue stress and injury, and elevated levels are associated with body weight loss in numerous chronic human diseases 8 , 9 . By isolating GFRAL as the receptor for GDF15-induced anorexia and weight loss, we identify a mechanistic basis for the non-homeostatic regulation of neural circuitry by a peripheral signal associated with tissue damage and stress. These findings provide opportunities to develop therapeutic agents for the treatment of disorders with altered energy demand.

In a similar study of ethnic differences of alcohol use on two college campuses in South Carolina, African American students enrolled at the majority Black institution were less likely to drink, and much less likely to drink to excess than the White students at a majority White institution (Hausman, 2002). Personal characteristics, (including genetics) and other attributes of the campus, including the external environment (i.e. bars, nightclubs,) physical aspects (geographic region, size, living arrangements for students,) and the socio-cultural environment (athletics, Greek organizations, traditions, and social norms and perceptions of drinking), all affect the rates of alcohol consumption on college and university campuses.

Nature 550, 255–259 (2017); doi:10.1038/nature24042 Owing to an error during the production process, in Fig. 2c of this Letter, all four groups of mice were incorrectly labelled as ‘WT’ (wild type), but the two groups on the left (filled and open blue boxes) should have been labelled ‘WT’, whereas the two groups on the right (filled and open yellow boxes) should have been labelled ‘KO’ (knockout), as in the key for Fig. 2b. The original Letter has been corrected online.

Alcohol continues to be a major concern on colleges and university campuses across the nation. Many efforts and innovative programs have been utilized within college and university campuses to help stop or prevent these escalating problems. The purpose of this investigation was to determine if there is a significant difference between the family influence, and ordinal sibling positions in relation to binge drinking, with special inferences between first and last-born students. This study investigated drinking propensities while currently attending the selected university. More specifically, this study was designed to determine the amount of weekly drinks, binge frequencies at a selected university in Texas. The CORE Alcohol and Drug instrument was to be used to determine the status or relationship between the variables; gender, ethnic origin, employment status, academic classification, living arrangements, age and martial status. The researcher's Birth Order survey was used for determining the respondent's birth position, family dynamics, income, and family sibling size. To test the hypotheses of this study, the researcher used a non-parametric test version of the one-way Analysis of Variance (ANOVA). The Kruskal-Wallis H analysis was used to test nominal categorical data for comparison between independent variables. The Kruskal-Wallis H test was utilized as a one-way between-subjects designed to test mean rank differences with ordinal ranked data. The measured variables were the number of self-reported weekly drinks and binge drinking frequencies, at probability levels of .05 or higher. Significant findings were reported on binge drinking differences between first and last-born positions, weekly average drinks were found among ethnicity and gender.

BackgroundLipid management is a key component of secondary prevention after acute coronary syndrome (ACS). In recent years, novel lipid-lowering therapies (LLTs) have emerged, including proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i, monoclonal antibodies and inclisiran),1 and icosapent ethyl (IPE) for hypertriglyceridaemia.2 3 Studies pre-dating these agents have reported poor secondary prevention lipid management in the United Kingdom.4 5 We aimed to assess and improve local lipid management in patients with ACS. Furthermore, we sought to assess real-world eligibility for inclisiran and IPE in this setting.MethodsConsecutive patients admitted with ACS in April-June 2022 (initial audit) and April-June 2024 (reassessment) were included. A PDSA approach was employed, with interim assessment, action plan formulation, and implementation. Quality metrics were assessed in line with NICE guideline NG238:6 i. Baseline assessment with a full lipid profile (including non-high-density lipoprotein cholesterol [non-HDL-C]), ii. Escalation of LLT to a maximum-dose high-intensity statin (e.g. atorvastatin 80mg) unless contraindicated, iii. Repeat full lipid profile assessment within three months post-discharge.Eligibility for inclisiran and IPE were assessed for the April-June 2024 cohort, following relevant NICE technology appraisals (TA733 and TA805).7 8 Abstract 7-024 Table 1Baseline characteristics. High-intensity defined as per NICE Guideline NG238, i.e. agent and dose with ≥40% low-density-lipoprotein cholesterol lowering capacity. CVD, cardiovascular disease, LLT, lipid-lowering therapy. Cycle 1 (n=97) Cycle 2 (n=102) Mean age, years (standard deviation) 67.7 (13.5) 69.6 (12.6) Female, n (%) 29 (30) 32 (31) Admission lipid-lowering therapy High-intensity LLT, n (%) 42 (43) 51 (50) Non-high-intensity LLT, n (%) 8 (8) 10 (10) No LLT, n (%) 48 (49) 41 (40) Co-morbidities/ cardiovascular risk factors Known CVD, n (%) 41 (42) 45 (44) Hypertension, n (%) 56 (58) 67 (66) Smoking history, n (%) 52 (54) 45 (44) Diabetes mellitus, n (%) 28 (29) 31 (30) Results97 and 102 eligible patients were identified (table 1). Key performance metrics are summarised in table 2. On initial audit, only 10% underwent full lipid profile testing on admission, and LLT was appropriately managed in 65%. After discharge, only 37% of patients underwent repeat non-HDL-C testing within three months.Abstract 7-024 Table 2Summary of performance in audited metrics across the two cycles. Statistical tests performed using the chi-squared test. Non-HDL-C, non-high-density lipoprotein cholesterol. Cycle 1 (n=97) Cycle 2 (n=102) P value Admission lipid profile testing Full lipid profile, n (%) 10 (10) 76 (75) <0.001 Total cholesterol only, n (%) 77 (80) 16 (16) Not assessed, n (%) 10 (10) 10 (10) Inpatient management of LLT Appropriate escalation/ management, n (%) 63 (65) 80 (78) 0.035 Inappropriate management, n (%) 34 (35) 22 (22) Outpatient re-assessment within 3 months Any repeat testing within 3 months , n (%) 52 (54) 70 (69) Repeat test with non-HDL-C within 3 months , n (%) 36 (37) 64 (63) <0.001 Our intervention included: i. inclusion of full lipid profiles in the ACS blood test careset, ii. resident doctor education, iii. use of a standardised discharge letter template, and iv. generation of a departmental guide for LLT.After intervention, there were significant improvements in admission full lipid profile testing (76/102, 75%, p<0.001), and LLT management (80/102, 80%, p=0.035). After discharge, a greater proportion of patients underwent repeat non-HDL-C assessment within three months (64/102, 63%, p<0.001).Using the last available full lipid profile, post-discharge therapeutic non-HDL-C control (<2.5 mmol/L) was achieved in a non-significant higher proportion of patients in cycle 2 (52/80 [65%], vs cycle 1 35/66 [53%], p=0.14). In cycle 2, 3% (2/80) of patients with repeat non-HDL-C were eligible for inclisiran, and 28% (13/47) with triglyceride re-measurement were eligible for IPE (figures 1 and 2).Abstract 7-024 Figure 1Eligibility for inclisiran. All measurements are in mmol/L. LDL-C, low-density lipoprotein cholesterol, non-HDL-C, non-high-density lipoprotein cholesterol. Images created with the assistance of SankeyMATIC.com.[Image Omitted. See PDF.]Abstract 7-024 Figure 2Eligibility for icosapent ethyl. All measurements are in mmol/L. IPE, icosapent ethyl, LDL-C, low-density lipoprotein cholesterol, non-HDL-C, non-high-density lipoprotein cholesterol, TG, triglycerides. Images created with the assistance of SankeyMATIC.com.[Image Omitted. See PDF.]ConclusionThrough structured intervention, we improved local lipid assessment and management in patients with ACS, with downstream effects on repeat testing, though further improvements are possible and required. A third of patients are not at target non-HDL-C at re-assessment. A quarter of re-assessed patients are eligible for triglyceride-lowering therapy.ReferencesRay KK, Wright RS, Kallend D, et al. Two phase 3 trials of inclisiran in patients with elevated LDL cholesterol. New Engl J Med 2020;382:1507–1519.Bhatt DL, Steg PG, Miller M, et al. Cardiovascular risk reduction with icosapent ethyl for hypertryglyceridaemia. New Engl J Med 2019;380:11–22.Gaba P, Bhatt DL, Steg PG, et al. Prevention of cardiovascular events and mortality with icosapent ethyl in patients with prior myocardial infarction. J Am Coll Cardiol 2022;79:1660–1671.Aubiniere-Robb L, Dickerson JE, Brady AJB. Lipid testing and treatment after acute myocardial infarction: no flags for the flagship. Br J Cardiol 2019;26:141–144.Salim HY, Lwin K, Khoo C, Wilson D. Management of hyperlipidaemia following acute coronary syndrome: a retrospective audit. Br J Cardiol 2021;28:62–66.Cardiovascular disease: risk assessment and reduction, including lipid modification (2023) NICE guideline NG238. Available from: https://www.nice.org.uk/guidance/ng238 Inclisiran for treating primary hypercholesterolaemia or mixed dyslipidaemia (2021) NICE TA 733. Available from: https://www.nice.org.uk/guidance/ta733 Icosapent ethyl with statin therapy for reducing the risk of cardiovascular events in people with raised triglycerides (2022) NICE TA 805. Available from: https://www.nice.org.uk/guidance/ta805

Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer and has a high risk of distant metastasis at every disease stage. We aimed to characterize the genomic landscape of LUAD and identify mutation signatures associated with tumor progression. We performed an integrative genomic analysis, incorporating whole exome sequencing (WES), determination of DNA copy number and DNA methylation, and transcriptome sequencing for 101 LUAD samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. We detected driver genes by testing whether the nonsynonymous mutation rate was significantly higher than the background mutation rate and replicated our findings in public datasets with 724 samples. We performed subclonality analysis for mutations based on mutant allele data and copy number alteration data. We also tested the association between mutation signatures and clinical outcomes, including distant metastasis, survival, and tumor grade. We identified and replicated two novel candidate driver genes, POU class 4 homeobox 2 (POU4F2) (mutated in 9 [8.9%] samples) and ZKSCAN1 (mutated in 6 [5.9%] samples), and characterized their major deleterious mutations. ZKSCAN1 was part of a mutually exclusive gene set that included the RTK/RAS/RAF pathway genes BRAF, EGFR, KRAS, MET, and NF1, indicating an important driver role for this gene. Moreover, we observed strong associations between methylation in specific genomic regions and somatic mutation patterns. In the tumor evolution analysis, four driver genes had a significantly lower fraction of subclonal mutations (FSM), including TP53 (p = 0.007), KEAP1 (p = 0.012), STK11 (p = 0.0076), and EGFR (p = 0.0078), suggesting a tumor initiation role for these genes. Subclonal mutations were significantly enriched in APOBEC-related signatures (p < 2.5×10-50). The total number of somatic mutations (p = 0.0039) and the fraction of transitions (p = 5.5×10-4) were associated with increased risk of distant metastasis. Our study's limitations include a small number of LUAD patients for subgroup analyses and a single-sample design for investigation of subclonality. These data provide a genomic characterization of LUAD pathogenesis and progression. The distinct clonal and subclonal mutation signatures suggest possible diverse carcinogenesis pathways for endogenous and exogenous exposures, and may serve as a foundation for more effective treatments for this lethal disease. LUAD's high heterogeneity emphasizes the need to further study this tumor type and to associate genomic findings with clinical outcomes.

Viral infection perturbs host cells and can be used to uncover regulatory mechanisms controlling cellular responses and susceptibility to infections. Using cell biological, biochemical, and genetic tools, we reveal that influenza A virus (IAV) infection induces global transcriptional defects at the 3′ ends of active host genes and RNA polymerase II (RNAPII) run-through into extragenic regions. Deregulated RNAPII leads to expression of aberrant RNAs (3′ extensions and host-gene fusions) that ultimately cause global transcriptional downregulation of physiological transcripts, an effect influencing antiviral response and virulence. This phenomenon occurs with multiple strains of IAV, is dependent on influenza NS1 protein, and can be modulated by SUMOylation of an intrinsically disordered region (IDR) of NS1 expressed by the 1918 pandemic IAV strain. Our data identify a strategy used by IAV to suppress host gene expression and indicate that polymorphisms in IDRs of viral proteins can affect the outcome of an infection.

Increasing awareness of the prevalence and significance of Preserved Ratio Impaired Spirometry (PRISm), alternatively known as restrictive or Global Initiative for Chronic Obstructive Lung Disease (GOLD)-unclassified spirometry, has expanded the body of knowledge on cross-sectional risk factors. However, longitudinal studies of PRISm remain limited. To examine longitudinal patterns of change in lung function, radiographic characteristics, and mortality of current and former smokers with PRISm. Current and former smokers, aged 45 to 80 years, were enrolled in COPDGene (phase 1, 2008-2011) and returned for a 5-year follow-up (phase 2, 2012-2016). Subjects completed questionnaires, spirometry, chest computed tomography scans, and 6-minute-walk tests at both study visits. Baseline characteristics, longitudinal change in lung function, and mortality were assessed by post-bronchodilator lung function categories: PRISm (FEV /FVC < 0.7 and FEV  < 80%), GOLD0 (FEV /FVC > 0.7 and FEV  > 80%), and GOLD1-4 (FEV /FVC < 0.7). Although the prevalence of PRISm was consistent (12.4-12.5%) at phases 1 and 2, subjects with PRISm exhibited substantial rates of transition to and from other lung function categories. Among subjects with PRISm at phase 1, 22.2% transitioned to GOLD0 and 25.1% progressed to GOLD1-4 at phase 2. Subjects with PRISm at both phase 1 and phase 2 had reduced rates of FEV decline (-27.3 ± 42.1 vs. -33.0 ± 41.7 ml/yr) and comparable proportions of normal computed tomography scans (51% vs. 52.7%) relative to subjects with stable GOLD0 spirometry. In contrast, incident PRISm exhibited accelerated rates of lung function decline. Subjects with PRISm at phase 1 had higher mortality rates relative to GOLD0 and lower rates relative to the GOLD1-4 group. PRISm is highly prevalent, is associated with increased mortality, and represents a transitional state for significant subgroups of subjects. Additional studies to characterize longitudinal progression in PRISm are warranted.

The genetic regulation of the human epigenome is not fully appreciated. Here we describe the effects of genetic variants on the DNA methylome in human lung based on methylation-quantitative trait loci (meQTL) analyses. We report 34,304 cis - and 585 trans -meQTLs, a genetic–epigenetic interaction of surprising magnitude, including a regulatory hotspot. These findings are replicated in both breast and kidney tissues and show distinct patterns: cis -meQTLs mostly localize to CpG sites outside of genes, promoters and CpG islands (CGIs), while trans -meQTLs are over-represented in promoter CGIs. meQTL SNPs are enriched in CTCF-binding sites, DNaseI hypersensitivity regions and histone marks. Importantly, four of the five established lung cancer risk loci in European ancestry are cis- meQTLs and, in aggregate, cis -meQTLs are enriched for lung cancer risk in a genome-wide analysis of 11,587 subjects. Thus, inherited genetic variation may affect lung carcinogenesis by regulating the human methylome. The effects of genetic variation on DNA methylation patterns are poorly understood. Here, Shi et al. systematically map methylation-quantitative trait loci in lung, breast and kidney tissue to reveal the impact of inherited variation on the human methylome, which also affects cancer risk.