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10.2337/dbi16-0069

http://scihub22266oqcxt.onion/10.2337/dbi16-0069
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C5482091!5482091!28603140
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suck abstract from ncbi

pmid28603140      Diabetes 2017 ; 66 (7): 1770-8
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  • Mining the Genome for Therapeutic Targets #MMPMID28603140
  • Florez JC
  • Diabetes 2017[Jul]; 66 (7): 1770-8 PMID28603140show ga
  • Current pharmacological options for type 2 diabetes do not cure the disease. Despite the availability of multiple drug classes that modulate glycemia effectively and minimize long-term complications, these agents do not reverse pathogenesis, and in practice they are not selected to correct the molecular profile specific to the patient. Pharmaceutical companies find drug development programs increasingly costly and burdensome, and many promising compounds fail before launch to market. Human genetics can help advance the therapeutic enterprise. Genomic discovery that is agnostic to preexisting knowledge has uncovered dozens of loci that influence glycemic dysregulation. Physiological investigation has begun to define disease subtypes, clarifying heterogeneity and suggesting molecular pathways for intervention. Convincing genetic associations have paved the way for the identification of effector transcripts that underlie the phenotype, and genetic or experimental proof of gain or loss of function in select cases has clarified the direction of effect to guide therapeutic development. Genetic studies can also examine off-target effects and furnish causal inference. As this information is curated and made widely available to all stakeholders, it is hoped that it will enhance therapeutic development pipelines by accelerating efficiency, maximizing cost-effectiveness, and raising ultimate success rates.
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