Implementing collaborative practices in the healthcare supply chain:insights into hospital-vendor operations

The paper discusses the characteristics of healthcare supply chains, and puts particular emphasis on the implementation of VMI/CMI in this sector specific context. By the means of case study research the paper provides empirical data on the benefits of the above collaborative practices for both the hospital and vendors. The paper contributes to the stream of research on VMI/CMI in the healthcare sector, where limited research attempts have been conducted so far. In contrast to other surveys this case study shows that specific and measurable cost reductions exist, in addition to other improvements such as better control over the inventories, and also in reduction of administrative work. Results obtained may be also relevant to other hospitals and vendors and as they can form a basis for comparisons

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Research data supporting: "Understanding the genetic complexity of puberty timing across the allele frequency spectrum"

This dataset is made up of GWAS meta-analysis for age at menarche (AAM), in up to 799,845 women. All studies provided GWAS data imputed to at least 1000 Genomes reference panel density, yielding a total of ~12.7 million genetic variants in the final meta-analysis. Variants were meta-analysed using a fixed-effects inverse-variance-weighted model in METAL and filtered to include minor allele frequency (MAF) >= 0.1%. Summary statistics made available for download are from an analysis excluding 23andMe (ancestry combined up to n=723,014 and European-only up to n=556,124) and following all the filtering steps as outlined above. Datasets available for download: 1) Ancestry combined GWAS summary statistics Menarche2024_AncestryCombined_RELEASE_EXC23andMe.txt.gz 2) European-only GWAS summary statistics Menarche2024_EuropeanOnly_RELEASE_EXC23andMe.txt.gz Both tab-delimited files, with one row per SNP including the same columns as the above. For further information please check the supplied readme file or the associated publication.MC_UU_00006/

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Acknowledgements: This research was supported by the UK Medical Research Council (MRC; Unit program MC_UU_00006/2) and has been conducted using the UK Biobank Resource under application 9905. Other study-specific acknowledgements can be found in the Supplementary Information.Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Acknowledgements: This research was supported by the UK Medical Research Council (MRC; Unit program MC_UU_00006/2) and has been conducted using the UK Biobank Resource under application 9905. Other study-specific acknowledgements can be found in the Supplementary Information.Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease