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Background Although genome-wide association studies (GWAS) of breast cancer (BC) identified common variants which differ between intrinsic subtypes, genes through which these variants act to impact BC risk have not been fully established. Transcriptome-wide association studies (TWAS) have identified genes associated with overall BC risk, but subtype-specific differences are largely unknown. Methods We performed two multi-tissue TWAS for each BC intrinsic subtype, including an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues and a novel splicing-based approach that collated signals from splicing QTLs (sQTLs) across intron clusters and subsequently across tissues. We used summary statistics for five intrinsic subtypes including Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, and triple-negative BC, generated from 106 278 BC cases and 91 477 controls in the Breast Cancer Association Consortium. Results Overall, we identified 235 genes in 88 loci that were associated with at least one of the five intrinsic subtypes. Most genes were subtype-specific, and many have not been reported in previous TWAS. We discovered common variants that modulate expression of CHEK2 confer increased risk to Luminal A-like BC, in contrast to the viewpoint that CHEK2 primarily harbors rare, penetrant mutations. Additionally, our splicing-based TWAS provided population-level support for MDM4 splice variants that increased the risk of triple-negative BC. Conclusion Our comprehensive, multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation that impacts expression and splicing of genes in multiple tissue types can be used to further elucidate the etiology of BC. [ABSTRACT FROM AUTHOR]

Background and Purpose: Thrombectomy for large vessel occlusion acute ischemic stroke (AIS-LVO) may benefit patients up to 24 hour since last known normal (LKN). Prehospital tools, like the Cincinnati Stroke Triage Assessment Tool (C-STAT), are used to select hospital destination for suspected AIS-LVO patients. The objective of this study was to estimate the potential impact of the expanded thrombectomy time window on suspected AIS-LVO cases transported to the regional comprehensive stroke center (CSC). Methods: From June to November 2015, C-STAT was performed by prehospital providers following a positive prehospital Cincinnati Prehospital Stroke Scale (CPSS) stroke screen in suspected stroke/TIA patients. There was no preferential triage based on C-STAT results. Final diagnoses, including the presence of AIS-LVO was ascertained via medical record review. Impact of positive C-STAT cases on CSC volumes was estimated for up to 24 hours since LKN. Results: Of 158 patients with prehospital suspicion for stroke/TIA, 105 were CPSS positive within 24 hours of onset and had complete C-STAT and clinical data available for analysis. Forty-six percent (17/37) of C-STAT + were non-strokes. C-STAT sensitivity and specificity for LVO were 71% (95% CI 36–92) and 67% (95% CI 58–80), respectively. C-STAT triage would increase transport of prehospital suspected stroke cases to the CSC by 11% (12/105) within six hours and 21% (22/105) within 24 hours. Of 37 C-STAT + patients, only 5 (13.5%) had LVO as final diagnosis. Conclusions: Preferential triage of prehospital suspected stroke patients using C-STAT would increase the number of patients transported to the CSC by 11% within six hours and an additional 10% from six to 24 hours. For every patient with LVO as final diagnosis, approximately an additional 6 non-LVO patients would be triaged to a CSC. [ABSTRACT FROM AUTHOR]

Introduction: Bipolar disorder is a complex psychiatric condition with distinctions between clinical subtypes including Type 1 and 2 disorders. Several studies have proposed that thyroid hormones may be involved in the aetiology of bipolar disorders., Methods: This study employed a two-sample Mendelian randomization (MR) approach to investigate the causal relationships between six thyroid hormone metrics (TSH, FT4, FT3, TT3, FT3/FT4 and TT3/FT4) and bipolar disorder and Type 1 and 2 disorders, separately. Genome-wide association (GWAS) data from the ThyroidOmics Consortium (up to 271,040 individuals of European ancestry) were used for thyroid function metrics. Bipolar disorder GWAS data included 41,917 cases and 371,549 controls (25,060 Type 1 and 6,781 Type 2 cases). We applied inverse variance weighted (IVW) methods for primary MR analysis, with MR Egger, weighted median and weighted mode for sensitivity. Additional tests assessed horizontal pleiotropy and heterogeneity., Results: Higher FT4 levels showed a protective causal effect against bipolar disorder (OR: 0.92, 95% CI: 0.86-0.97, p = 4.58 × 10 -3 ) and a suggestive effect on Type 1 disorders (OR: 0.92, 95% CI: 0.86-0.99, p = 3.21 × 10 -2 ). Elevated FT3 (OR: 1.18, 95% CI: 1.03-1.35, p = 1.55 × 10 -2 ) and FT3/FT4 ratio (OR: 1.97, 95% CI: 1.02-3.82, p = 4.46 × 10 -2 ) had suggestive harmful effects on Type 1 disorders. Sensitivity analyses showed consistent effects, with no significant horizontal pleiotropy or heterogeneity., Conclusions: These findings highlight the protective role of FT4 and the potentially harmful effect of elevated FT3 in Type 1 bipolar disorder, highlighting the need for further research on thyroid hormone levels as a potential treatment strategy for Type 1 bipolar disorder., (© 2024 The Author(s). Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.)