Advances in the targeted theragnostics of osteomyelitis caused by Staphylococcus aureus.

Bone infections caused by Staphylococcus aureus may lead to an inflammatory condition called osteomyelitis, which results in progressive bone loss. Biofilm formation, intracellular survival, and the ability of S. aureus to evade the immune response result in recurrent and persistent infections that present significant challenges in treating osteomyelitis. Moreover, people with diabetes are prone to osteomyelitis due to their compromised immune system, and in life-threatening cases, this may lead to amputation of the affected limbs. In most cases, bone infections are localized; thus, early detection and targeted therapy may prove fruitful in treating S. aureus-related bone infections and preventing the spread of the infection. Specific S. aureus components or overexpressed tissue biomarkers in bone infections could be targeted to deliver active therapeutics, thereby reducing drug dosage and systemic toxicity. Compounds like peptides and antibodies can specifically bind to S. aureus or overexpressed disease markers and combining these with therapeutics or imaging agents can facilitate targeted delivery to the site of infection. The effectiveness of photodynamic therapy and hyperthermia therapy can be increased by the addition of targeting molecules to these therapies enabling site-specific therapy delivery. Strategies like host-directed therapy focus on modulating the host immune mechanisms or signaling pathways utilized by S. aureus for therapeutic efficacy. Targeted therapeutic strategies in conjunction with standard surgical care could be potential treatment strategies for S. aureus-associated osteomyelitis to overcome antibiotic resistance and disease recurrence. This review paper presents information about the targeting strategies and agents for the therapy and diagnostic imaging of S. aureus bone infections.

Human Genetics and Genomics for Drug Target Identification and Prioritization: Open Targets' Perspective.

Open Targets, a consortium among academic and industry partners, focuses on using human genetics and genomics to provide insights to key questions that build therapeutic hypotheses. Large-scale experiments generate foundational data, and open-source informatic platforms systematically integrate evidence for target-disease relationships and provide dynamic tooling for target prioritization. A locus-to-gene machine learning model uses evidence from genome-wide association studies (GWAS Catalog, UK BioBank, and FinnGen), functional genomic studies, epigenetic studies, and variant effect prediction to predict potential drug targets for complex diseases. These predictions are combined with genetic evidence from gene burden analyses, rare disease genetics, somatic mutations, perturbation assays, pathway analyses, scientific literature, differential expression, and mouse models to systematically build target-disease associations (https://platform.opentargets.org). Scored target attributes such as clinical precedence, tractability, and safety guide target prioritization. Here we provide our perspective on the value and impact of human genetics and genomics for generating therapeutic hypotheses.

Genome-wide association study analysis of disease severity in Acne reveals novel biological insights.

Acne vulgaris is a common skin disease that affects >85% of teenage young adults among which >8% develop severe lesions that leaves permanent scars. Genetic heritability studies of acne in twin cohorts have estimated that the heritability for acne is 80%. Previous genome-wide association studies (GWAS) have identified 50 genetic loci associated with increased risk of developing acne when compared to healthy individuals. However only a few studies have investigated genetic association with disease severity. GWAS of disease progression may provide a more effective approach to unveil potential disease modifying therapeutic targets. Here, we performed a multi-ethnic GWAS analysis to capture disease severity in acne patients by using individuals with normal acne as a control. Our cohort consists of a total of 2,956 participants, including 290 severe acne cases and 930 normal acne controls from FinnGen, and 522 cases and 1,214 controls from BioVU. We also performed mendelian randomization (MR), colocalization analyses and transcriptome-wide association study (TWAS) to identify putative causal genes. Lastly, we performed gene-set enrichment analysis using MAGMA to implicate biological pathways that drive disease severity in Acne. We identified two new loci associated with acne severity at the genome-wide significance level, six novel associated genes by MR, colocalization and TWAS analyses, including genes CDC7, SLC7A1, ADAM23, TTLL10, CDK20 and DNAJA4 , and 5 novel pathways by MAGMA analyses. Our study suggests that the etiologies of acne susceptibility and severity have limited overlap, with only 26% of known acne risk loci presenting nominal association with acne severity and none of the novel severity associated genes reported as associated with acne risk in previous GWAS.