Irene Serrano-Gonzalo

The clinical heterogeneity of type 1 Gaucher disease (GD1) underscores the limited correlation between the GBA1 genotype and phenotype. This study examined GD1 patients from the Spanish Gaucher Disease Registry carrying heterozygous GBA1 genotypes distinct from NM_000157: c.[1226A>G](N370S); [1448T>C](L444P). Among 374 patients with GD1, 195 (52.1%) had alternative heterozygous combinations, including variants corresponding to severe (37.9%) or moderate (42.1%) mutation, whereas only 20% patients harbored mild variants—all of them in combination with N370S. Descriptive statistics and predictive models based on logistic regression and decision trees were applied. Patients carrying N370S with a different L444P variant showed significantly higher rates of advanced bone disease (59.9%) compared to those with homozygous N370S (38.3%) or N370S; L444P (41.0%) (p = 0.002). Decision tree analysis identified the bone marrow burden score (S-MRI) as the strongest predictor of osteopenia/osteoporosis at diagnosis. Genotype also emerged as a key discriminator for Parkinson’s disease: patients with non-N370S; L444P genotypes showed a markedly higher likelihood of developing Parkinsonism. Overall, GD1 patients with genotypes other than N370S; L444P present more severe phenotypes, particularly with greater skeletal involvement and neurological complications. These findings highlight the importance of genotype stratification and predictive modeling in improving risk assessment and clinical management in GD1.

Bone manifestations are one of the most prevalent complications in patients with Gaucher disease (GD). Bone involvement is evaluated by using imaging methods, and there are different scores to assess its severity. However, there are no biomarkers that allow us to predict these manifestations. In recent years, several miRNAs have been associated with bone involvement and postulated as excellent bioavailable biomarkers. This study aims to identify a miRNA expression profile from plasma exosomes and to associate it with the severity of bone involvement in patients with GD. This study included 60 untreated patients with GD with bone involvement, who were classified according to the S‐MRI score into three groups: mild disease (MiBD; S‐MRI < 5), moderate disease (MoBD; S‐MRI: 5–11), or severe disease (SBD; S‐MRI > 11). Plasma exosomes were purified, and miRNAs were extracted and identified by next‐generation sequencing (NGS) technology. Differentially expressed miRNAs were validated by droplet digital PCR (ddPCR). In the patients' groups classified by S‐MRI, the median ages (Q1–Q3) were: MiBD 19.0 (4.00–40.00), MoBD 40.5 (28.25–56.00), and SBD 37.5 (31.25–47.00) years. When comparing groups, we found 12 differentially expressed exosomal miRNAs. After validation, four miRNAs were identified as differentially expressed: hsa‐miR‐127‐3p, hsa‐miR‐184, hsa‐miR‐197‐3p, and hsa‐miR‐660‐5p. Notably, hsa‐miR‐127‐3p, hsa‐miR‐660‐5p, and hsa‐miR‐184 were correlated with the presence of infarcts, necrosis, and the degree of infiltration into the spine, pelvis, and femur. These three miRNAs could serve as bioavailable biomarkers to assess bone disease in GD, and further revalidation with a higher number of patients.

Lysosomal acid lipase deficiency (LAL-D) is an ultra-rare lysosomal storage disease with two distinct phenotypes, an infantile-onset form (formerly Wolman disease) and a later-onset form (formerly cholesteryl ester storage disease). The objective of this narrative review is to examine the most important aspects of the diagnosis and treatment of LAL-D and to provide practical expert recommendations. The infantile-onset form occurs in the first weeks of life and is characterized by malnourishment and failure to thrive due to gastrointestinal impairment (vomiting, diarrhea, malabsorption), as well as systemic inflammation, hepatosplenomegaly, and adrenal calcifications. Mortality is close to 100% before one year of life in the absence of specific treatment. The later-onset form can be diagnosed in childhood or adulthood and is characterized by chronic liver injury and/or lipid profile alterations. When LAL-D is suspected, enzyme activity should be determined to confirm the diagnosis, with analysis from a dried blood spot sample being the quickest and most reliable method. In infantile-onset LAL-D, the initiation of enzyme replacement therapy (sebelipase α) and careful nutritional management with a low-lipid diet is very urgent, as prognosis is directly linked to the early initiation of specific treatment. In recent years, our knowledge of the management of LAL-D has increased considerably, with improvements regarding the initial enzyme replacement therapy dose and careful nutritional treatment with a low-lipid diet to decrease lipid deposition and systemic inflammation, leading to better outcomes. In this narrative review we offer a quick guide for the initial management of infantile-onset LAL-D.

Multiple myeloma is an incurable cancer of plasma cells that depends on the bone marrow for its survival. Despite its prevalence, the molecular mechanisms underlying this malignancy remain poorly understood. In this study, we aim to bridge this knowledge gap by elucidating the metabolic interplay between myeloma cells and bone marrow mesenchymal stem cells (BMMSCs). BMMSCs are crucial in supporting myeloma cell metabolism, contributing to their proliferation, survival, and resistance to chemotherapy. Through a combination of mathematical modelling and experimental co-cultures, we demonstrate that pyruvate – the end product of glycolysis – plays a key role in myeloma cell metabolism. Our findings reveal that myeloma cells predominantly rely on the uptake of pyruvate produced by neighbouring BMM-SCs via the plasma membrane proton-linked monocarboxylate transporters MCT-1 and MCT-2 encoded by the Slc16a1 and a2 genes, respectively. Furthermore, we show that pharmacological inhibition of the MCT-1/2, with AZD3965, triggers a cascade of compensatory metabolic responses, disrupting redox balance and significantly reducing the proliferation capacity of co-cultured myeloma cells.

It is increasingly apparent that cancer cells, in addition to remodelling their metabolism to survive and proliferate, adapt and manipulate the metabolism of other cells. This property may be a telling sign that pre-clinical tumour metabolism studies that exclusively utilise in-vitro mono-culture models could prove to be limited for uncovering novel metabolic targets that can translate into clinical therapies. Although this is increasingly recognised, and work addressing this is becoming routinary in a rapidly emerging field, much remains unknown. This study employs an interdisciplinary approach that leverages the predictive power of mathematical modelling to enrich experimental findings. We develop a functional multicellular in-silico model that facilitates the qualitative and quantitative analysis of the metabolic network spawned by an in-vitro co-culture model of bone marrow mesenchymal stem- and myeloma cell lines. To procure this model, we devised a bespoke human genome constraint-based reconstruction workflow that combines aspects from the legacy mCADRE & Metabotools algorithms, the novel redHuman algorithm, along with ¹³ C-metabolic flux analysis. Our workflow transforms the latest human metabolic network matrix (Recon3D) into two cell-specific models coupled with a metabolic network spanning a shared growth medium. When cross-validating our in-silico model against the in-vitro model, we found that the in-silico model successfully reproduces vital metabolic behaviours of its in-vitro counterpart; results include cell growth predictions, respiration rates, as well as support for observations which suggest cross-shuttling of redox-active metabolites between cells. Together, our methodology and its results provide yet another step toward the relevance of studies of this type in the field.

Background: Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the disease have changed. However, there remain unmet needs such as the identification of patients at risk of developing bone crisis during therapy and late complications such as cancer or parkinsonism. The Spanish Gaucher Disease Registry has worked since 1993 to compile demographic, clinical, genetic, analytical, imaging and follow-up data from more than 400 patients. The aims of this study were to discover correlations between patients’ characteristics at diagnosis and to identify risk features for the development of late complications; for this a machine learning approach involving correlation networks and decision trees analyses was applied. Results: A total of 358 patients, 340 type 1 Gaucher disease and 18 type 3 cases were selected. 18% were splenectomyzed and 39% had advanced bone disease. 81% of cases carried heterozygous genotype. 47% of them were diagnosed before the year 2000. Mean age at diagnosis and therapy were 28 and 31.5 years old (y.o.) respectively. 4% developed monoclonal gammopathy undetermined significance or Parkinson Disease, 6% cancer, and 10% died before this study. Previous splenectomy correlates with the development of skeletal complications and severe bone disease (p = 0.005); serum levels of IgA, delayed age at start therapy (> 9.5 y.o. since diagnosis) also correlates with severe bone disease at diagnosis and with the incidence of bone crisis during therapy. High IgG (> 1750 mg/dL) levels and age over 60 y.o. at diagnosis were found to be related with the development of cancer. When modelling the decision tree, patients with a delayed diagnosis and therapy were the most severe and with higher risk of complications. Conclusions: Our work confirms previous observations, highlights the importance of early diagnosis and therapy and identifies new risk features such as high IgA and IgG levels for long-term complications.