SRShola Michelle Richards

Shola Michelle Richards

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Shola Michelle Richards has a total of 62 co-authors. Here are the top co-authors by number of shared publications:

  • Agustin Albillos

    CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas) Barcelona Spain

    1 shared publication
  • Alexandra Aebi

    Novartis Biomedical Research Novartis Pharma AG Basel Switzerland

    1 shared publication
  • Alok Pachori

    Novartis Institutes for Biomedical Research East Hannover New Jersey USA

    1 shared publication
  • Andreas W. Sailer

    Disease Area X, Novartis Institutes for BioMedical Research, Basel, Switzerland

    1 shared publication
  • Anna Baiges

    Barcelona Hepatic Hemodynamic Laboratory Barcelona Health Care Provider of the European Reference Network on Rare Liver Barcelona Spain

    1 shared publication
  • Annette Begrich

    Novartis Biomedical Research Novartis Pharma AG Basel Switzerland

    1 shared publication

Latest Publications

  • Open Access

    Molecular characterization of chronic cutaneous wounds reveals subregion‐ and wound type‐specific differential gene expression

    by Shola Michelle Richards, Caroline Gubser Keller, Robert Kreutzer, Géraldine Greiner, Svenja Ley, Arno Doelemeyer, Valerie Dubost, Thierry Flandre, Susan Kirkland, Walter Carbone, et al.

    A limited understanding of the pathology underlying chronic wounds has hindered the development of effective diagnostic markers and pharmaceutical interventions. This study aimed to elucidate the molecular composition of various common chronic ulcer types to facilitate drug discovery strategies. We conducted a comprehensive analysis of leg ulcers (LUs), encompassing venous and arterial ulcers, foot ulcers (FUs), pressure ulcers (PUs), and compared them with surgical wound healing complications (WHCs). To explore the pathophysiological mechanisms and identify similarities or differences within wounds, we dissected wounds into distinct subregions, including the wound bed, border, and peri‐wound areas, and compared them against intact skin. By correlating histopathology, RNA sequencing (RNA‐Seq), and immunohistochemistry (IHC), we identified unique genes, pathways, and cell type abundance patterns in each wound type and subregion. These correlations aim to aid clinicians in selecting targeted treatment options and informing the design of future preclinical and clinical studies in wound healing. Notably, specific genes, such as PITX1 and UPP1, exhibited exclusive upregulation in LUs and FUs, potentially offering significant benefits to specialists in limb preservation and clinical treatment decisions. In contrast, comparisons between different wound subregions, regardless of wound type, revealed distinct expression profiles. The pleiotropic chemokine‐like ligand GPR15L (C10orf99) and transmembrane serine proteases TMPRSS11A/D were significantly upregulated in wound border subregions. Interestingly, WHCs exhibited a nearly identical transcriptome to PUs, indicating clinical relevance. Histological examination revealed blood vessel occlusions with impaired angiogenesis in chronic wounds, alongside elevated expression of genes and immunoreactive markers related to blood vessel and lymphatic epithelial cells in wound bed subregions. Additionally, inflammatory and epithelial markers indicated heightened inflammatory responses in wound bed and border subregions and reduced wound bed epithelialization. In summary, chronic wounds from diverse anatomical sites share common aspects of wound pathophysiology but also exhibit distinct molecular differences. These unique molecular characteristics present promising opportunities for drug discovery and treatment, particularly for patients suffering from chronic wounds. The identified diagnostic markers hold the potential to enhance preclinical and clinical trials in the field of wound healing.


  • Open Access

    Non‐invasive candidate protein signature predicts hepatic venous pressure gradient reduction in cirrhotic patients after sustained virologic response

    by Shola M. Richards, Fang Guo, Heng Zou, Florian Nigsch, Anna Baiges, Alok Pachori, Yiming Zhang, Sabela Lens, Rebecca Pitts, Nancy Finkel, et al.

    Background and Aims: A reduction in hepatic venous pressure gradient (HVPG) is the most accurate marker for assessing the severity of portal hypertension and the effectiveness of intervention treatments. This study aimed to evaluate the prognostic potential of blood‐based proteomic biomarkers in predicting HVPG response amongst cirrhotic patients with portal hypertension due to Hepatitis C virus (HCV) and had achieved sustained virologic response (SVR).Methods: The study comprised 59 patients from two cohorts. Patients underwent paired HVPG (pretreatment and after SVR), liver stiffness (LSM), and enhanced liver fibrosis scores (ELF) measurements, as well as proteomics‐based profiling on serum samples using SomaScan® at baseline (BL) and after SVR (EOS). Machine learning with feature selection (Caret, Random Forest and RPART) methods were performed to determine the proteins capable of classifying HVPG responders. Model performance was evaluated using AUROC (pROC R package).Results: Patients were stratified by a change in HVPG (EOS vs. BL) into responders (greater than 20% decline in HVPG from BL, or 10 mmHg at BL) and non‐responders. LSM and ELF decreased markedly after SVR but did not correlate with HVPG response. SomaScan (SomaLogic, Inc., Boulder, CO) analysis revealed a substantial shift in the peripheral proteome composition, reflected by 82 significantly differentially abundant proteins. Twelve proteins accurately distinguished responders from non‐responders, with an AUROC of .86, sensitivity of 83%, specificity of 83%, accuracy of 83%, PPV of 83%, and NPV of 83%.Conclusions: A combined non‐invasive soluble protein signature was identified, capable of accurately predicting HVPG response in HCV liver cirrhosis patients after achieving SVR.