Nonalcoholic fatty liver disease (NAFLD) is a common cause of chronic liver disease. A single‐nucleotide polymorphism (SNP), rs6834314, was associated with serum liver enzymes in the general population, presumably reflecting liver fat or injury. We studied rs6834314 and its nearest gene, 17‐beta hydroxysteroid dehydrogenase 13 (HSD17B13), to identify associations with histological features of NAFLD and to characterize the functional role of HSD17B13 in NAFLD pathogenesis. The minor allele of rs6834314 was significantly associated with increased steatosis but decreased inflammation, ballooning, Mallory‐Denk bodies, and liver enzyme levels in 768 adult Caucasians with biopsy‐proven NAFLD and with cirrhosis in the general population. We found two plausible causative variants in the HSD17B13 gene. rs72613567, a splice‐site SNP in high linkage with rs6834314 (r2 = 0.94) generates splice variants and shows a similar pattern of association with NAFLD histology. Its minor allele generates simultaneous expression of exon 6‐skipping and G‐nucleotide insertion variants. Another SNP, rs62305723 (encoding a P260S mutation), is significantly associated with decreased ballooning and inflammation. Hepatic expression of HSD17B13 is 5.9‐fold higher (P = 0.003) in patients with NAFLD. HSD17B13 is targeted to lipid droplets, requiring the conserved amino acid 22‐28 sequence and amino acid 71‐106 region. The protein has retinol dehydrogenase (RDH) activity, with enzymatic activity dependent on lipid droplet targeting and cofactor binding site. The exon 6 deletion, G insertion, and naturally occurring P260S mutation all confer loss of enzymatic activity. Conclusion: We demonstrate the association of variants in HSD17B13 with specific features of NAFLD histology and identify the enzyme as a lipid droplet–associated RDH; our data suggest that HSD17B13 plays a role in NAFLD through its enzymatic activity.

The second messenger cyclic diguanylate (c-di-GMP) controls the transition between motile and sessile growth in eubacteria, but little is known about the proteins that sense its concentration. Bioinformatics analyses suggested that PilZ domains bind c-di-GMP and allosterically modulate effector pathways. We have determined a 1.9 Å crystal structure of c-di-GMP bound to VCA0042/PlzD, a PilZ domain-containing protein from Vibrio cholerae. Either this protein or another specific PilZ domain-containing protein is required for V. cholerae to efficiently infect mice. VCA0042/PlzD comprises a C-terminal PilZ domain plus an N-terminal domain with a similar b-barrel fold. C-di-GMP contacts seven of the nine strongly conserved residues in the PilZ domain, including three in a seven-residue long N-terminal loop that undergoes a conformational switch as it wraps around c-di-GMP. This switch brings the PilZ domain into close apposition with the N-terminal domain, forming a new allosteric interaction surface that spans these domains and the c-di-GMP at their interface. The very small size of the N-terminal conformational switch is likely to explain the facile evolutionary diversification of the PilZ domain.

Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course.

Crystallization has proven to be the most significant bottleneck to high-throughput protein structure determination using diffraction methods. We have used the large-scale, systematically generated experimental results of the Northeast Structural Genomics Consortium to characterize the biophysical properties that control protein crystallization. Datamining of crystallization results combined with explicit folding studies lead to the conclusion that crystallization propensity is controlled primarily by the prevalence of well-ordered surface epitopes capable of mediating interprotein interactions and is not strongly influenced by overall thermodynamic stability. These analyses identify specific sequence features correlating with crystallization propensity that can be used to estimate the crystallization probability of a given construct. Analyses of entire predicted proteomes demonstrate substantial differences in the bulk amino acid sequence properties of human versus eubacterial proteins that reflect likely differences in their biophysical properties including crystallization propensity. Finally, our thermodynamic measurements enable critical evaluation of previous claims regarding correlations between protein stability and bulk sequence properties, which generally are not supported by our dataset. NIH Public Access Author ManuscriptNat Biotechnol. Author manuscript; available in PMC 2010 January 1. Published in final edited form as:Nat Biotechnol. 2009 January ; 27(1): 51-57. doi:10.1038/nbt.1514. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptThe ability to determine the atomic structures of macromolecules represents a great achievement in molecular biology because of the unparalleled value of this information in understanding the fundamental chemistry of life [1][2][3][4][5] . While nuclear magnetic resonance represents an invaluable source of structural information, especially for small proteins, most macromolecular structures are determined using x-ray crystallography. Capitalizing on the recent proliferation of genomic sequence data, "structural genomics" consortia have been organized worldwide to develop methods and infrastructure for high-throughput protein structure determination. These groups have contributed to improvements in expression and structure determination methods 6 , and the four largest U.S. consortia accounted for 45% of all novel structures deposited in the Protein Data Bank (PDB) in 2007 7 . While these efforts contribute to the impressive progress of the structural biology community in characterizing the full repertoire of protein structures, the rate of growth in sequence information nonetheless far out-paces that of structural information. Given the ongoing acceleration of whole-genome sequencing, the gap between the two will continue to expand without a breakthrough in macromolecular structure determination methods.The systematic efforts of structural genomics projects show that crystallization is the major bottleneck to protein structure determinati...

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the NIH Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly translated to clinical care. Unfortunately, traditional drug discovery methods have a >90% failure rate and can take 10-15 years from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious single agents and combination therapies against SARS-CoV-2. Quantitative high-content morphological profiling was coupled with an AI-based machine learning strategy to classify features of cells for infection and stress. This assay detected multiple antiviral mechanisms of action (MOA), including inhibition of viral entry, propagation, and modulation of host cellular responses. From a library of 1,425 FDA-approved compounds and clinical candidates, we identified 16 dose-responsive compounds with antiviral effects. In particular, we discovered that lactoferrin is an effective inhibitor of SARS-CoV-2 infection with an IC50 of 308 nM and that it potentiates the efficacy of both remdesivir and hydroxychloroquine. Lactoferrin also stimulates an antiviral host cell response and retains inhibitory activity in iPSC-derived alveolar epithelial cells, a model for the primary site of infection. Given its safety profile in humans, these data suggest that lactoferrin is a readily translatable therapeutic adjunct for COVID-19. Additionally, several commonly prescribed drugs were found to exacerbate viral infection and warrant clinical investigation. We conclude that morphological profiling for drug repurposing is an effective strategy for the selection and optimization of drugs and drug combinations as viable therapeutic options for COVID-19 pandemic and other emerging infectious diseases.

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The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10 to 15 y from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 US Food and Drug Administration (FDA)-approved compounds and clinical candidates, we identified 17 hits that inhibited SARS-CoV-2 infection and analyzed their antiviral activity across multiple cell lines, including lymph node carcinoma of the prostate (LNCaP) cells and a physiologically relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein found in secretory fluids including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19.