Native myocardial T1 and right ventricular size by CMR predict outcome in systemic sclerosis-associated pulmonary hypertension.

OBJECTIVES: Measures of right heart size and function are prognostic in systemic sclerosis-associated pulmonary hypertension (SSc-PH), but the importance of myocardial tissue characterisation remains unclear. We aimed to investigate the predictive potential and interaction of cardiovascular magnetic resonance (CMR) myocardial tissue characterisation and right heart size and function in SSc-PH. METHODS: A retrospective, single-centre, observational study of 148 SSc-PH patients confirmed by right heart catheterization who underwent clinically-indicated CMR including native myocardial T1 and T2 mapping from 2016 to 2023 was performed. RESULTS: Sixty-six (45%) patients died during follow-up (median 3.5 years, range 0.1-7.3). Patients who died were older (65 vs 60 years, p= 0.035) with more dilated (RVEDVi and RVESVi, p< 0.001), hypertrophied (RVMi, p= 0.013) and impaired (RVEF, p< 0.001) right ventricles, more dilated right atria (RAi, p= 0.043) and higher native myocardial T1 (p< 0.001).After adjustment for age, RVESVi (p = 0.0023) and native T1 (p = 0.0024) were independent predictors of all-cause mortality. Both RVESVi and native T1 remained independently predictive after adjusting for age and PH subtype (RVESVi p < 0.001, T1 p = 0.0056). Optimal prognostic thresholds for RVESVi and native T1 were ≤38 mL/m2 and ≤1119 ms, respectively (p < 0.001). Patients with RVESVi ≤ 38 mL/m2 and native T1 ≤ 1119 ms had significantly better outcomes than all other combinations (p < 0.001). Furthermore, patients with RVESVi > 38mL/m2 and native T1 ≤ 1119 ms had significantly better survival than patients with RVESVi > 38mL/m2 and native T1 > 1119ms (p = 0.017). CONCLUSION: We identified prognostically relevant CMR metrics and thresholds for patients with SSc-PH. Assessing myocardial tissue characterisation alongside RV function confers added value in SSc-PH and may represent an additional treatment target.

Artificial intelligence and machine learning for clinical pharmacology.

Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug discovery and development, clinical trials, personalized medicine, pharmacogenomics, pharmacovigilance and clinical toxicology. The rapid progress of AI in healthcare means clinical pharmacologists should have an understanding of AI and its implementation in clinical practice. As with any new therapy or health technology, it is imperative that AI tools are subject to robust and stringent evaluation to ensure that they enhance clinical practice in a safe and equitable manner. This review serves as an introduction to AI for the clinical pharmacologist, highlighting current applications, aspects of model development and issues surrounding evaluation and deployment. The aim of this article is to empower clinical pharmacologists to embrace and lead on the safe and effective use of AI within healthcare.

Clinical and pathogenic significance of S100A4 overexpression in systemic sclerosis.

OBJECTIVES: We have studied the damage-associated molecular pattern protein S100A4 as a driver of fibroblast activation in systemic sclerosis (SSc). METHODS: S100A4 protein concentration was measured by ELISA in serum of SSc (n=94) and healthy controls (n=15). Protein expression in skin fibroblast cultures from diffuse cutaneous SSc (SScF, n=6) and healthy controls (normal fibroblasts (NF), n=6) was assessed. Recombinant S100A4 and a high affinity anti-S100A4 neutralising monoclonal antibody (AX-202) were tested on SScF and NF. RESULTS: Median (range) S100A4 (ng/mL) was higher in serum of SSc (89.9 (15.0-240.0)) than healthy controls (71.4 (7.9-131.8); p=0.027). There was association with SSc-interstitial lung disease (p=0.025, n=55), scleroderma renal crisis (p=0.026, n=4). Median (range) S100A4 (ng/mL) was higher in culture supernatants of SScF (4.19 (0.52-8.42)) than NF controls (0.28 (0.02-3.29); p<0.0001). AX-202 reduced the constitutive profibrotic gene and protein expression phenotype of SScF. Genome-wide RNA sequencing analysis identified an S100A4 activated signature in NF overlapping the hallmark gene expression signature of SScF. Thus, 464 differentially expressed genes (false discovery rate (FDR) <0.001 and fold change (FC) >1.5) induced in NF by S100A4 were also constitutively overexpressed, and downregulated by AX-202, in SScF. Pathway mapping of these S100A4 dependent genes in SSc showed the most significant enriched Kegg pathways (FDR <0.001) were regulation of stem cell pluripotency (4.6-fold) and metabolic pathways (1.9-fold). CONCLUSION: Our findings provide compelling evidence for a profibrotic role for S100A4 in SSc and suggest that serum level may be a biomarker of major organ manifestations and disease severity. This study supports examining the therapeutic potential of targeting S100A4 in SSc.

A Phenome-Wide Association Study of Drugs and Comorbidities Associated With Gastrointestinal Dysfunction in Systemic Sclerosis.

OBJECTIVE: To explore the causes of and contributors to gastrointestinal (GI) dysfunction in systemic sclerosis (SSc) in a phenome-wide association study (PheWAS), using real-world clinical records data. METHODS: Twelve thousand five hundred thirty-five documented clinical assessments of 2058 consenting individuals with SSc at the Royal Free Hospital (UK) were available for detailed phenotyping. Diagnoses and drugs were mapped to structured dictionaries of terms (Disease Ontology project and DrugBank Open Data, respectively). A PheWAS model was used to explore links between 6 important SSc-GI domains (constipation, diarrhea, dysmotility, incontinence, gastroesophageal reflux, and small intestinal bacterial overgrowth [SIBO]) and exposure to various comorbidities and drugs. "Hits" from the PheWAS model were confirmed and explored in a subcohort reporting quantitative GI symptom scores from the University of California Los Angeles Scleroderma Clinical Trials Consortium Gastrointestinal Tract Instrument 2.0 (GIT 2.0) questionnaire. RESULTS: One thousand five hundred forty-six individuals were entered into the PheWAS analysis. Six hundred seventy-three distinct diagnoses and 634 distinct drugs were identified in the dataset, as well as SSc-specific phenotypes such as antinuclear antibodies (ANA). PheWAS analysis revealed associations between drugs, diagnoses, and ANAs with 6 important SSc-GI outcomes: constipation, diarrhea, dysmotility, incontinence, reflux, and SIBO. Subsequently, using GIT 2.0 symptom scores links with SSc-GI were confirmed for 22 drugs, 4 diagnoses, and 3 ANAs. CONCLUSION: Using a hypothesis-free PheWAS approach, we replicated known, and revealed potential novel, risk factors for SSc-GI dysfunction, including drug classes such as opioid, antimuscarinic, and endothelin receptor antagonist, and ANA subgroup.

Distinct cardiovascular phenotypes are associated with prognosis in systemic sclerosis: a cardiovascular magnetic resonance study.

AIMS: Cardiovascular involvement in systemic sclerosis (SSc) is heterogeneous and ill-defined. This study aimed to: (i) discover cardiac phenotypes in SSc by cardiovascular magnetic resonance (CMR); (ii) provide a CMR-based algorithm for phenotypic classification; and (iii) examine for associations between phenotypes and mortality. METHODS AND RESULTS: A retrospective, single-centre, observational study of 260 SSc patients who underwent clinically indicated CMR including native myocardial T1 and T2 mapping from 2016 to 2019 was performed. Agglomerative hierarchical clustering using only CMR variables revealed five clusters of SSc patients with shared CMR characteristics: dilated right hearts with right ventricular failure (RVF); biventricular failure dilatation and dysfunction (BVF); and normal function with average cavity (NF-AC), normal function with small cavity (NF-SC), and normal function with large cavity (NF-LC) sizes. Phenotypes did not co-segregate with clinical or antibody classifications. A CMR-based decision tree for phenotype classification was created. Sixty-three (24%) patients died during a median follow-up period of 3.4 years. After adjustment for age and presence of pulmonary hypertension (PH), independent CMR predictors of all-cause mortality were native T1 (P < 0.001) and right ventricular ejection fraction (RVEF) (P = 0.0032). NF-SC and NF-AC groups had more favourable prognoses (P≤0.036) than the other three groups which had no differences in prognoses between them (P > 0.14). Hazard ratios (HR) were statistically significant for RVF (HR = 8.9, P < 0.001), BVF (HR = 5.2, P = 0.006), and NF-LC (HR = 4.9, P = 0.002) groups. The NF-LC group remained significantly predictive of mortality after adjusting for RVEF, native T1, and PH diagnosis (P = 0.0046). CONCLUSION: We identified five CMR-defined cardiac SSc phenotypes that did not co-segregate with clinical data and had distinct outcomes, offering opportunities for a more precision-medicine based management approach.

Characteristics of adults with type 1 diabetes and treatment-resistant problematic hypoglycaemia: a baseline analysis from the HARPdoc RCT.

AIMS/HYPOTHESIS: Problematic hypoglycaemia still complicates insulin therapy for some with type 1 diabetes. This study describes baseline emotional, cognitive and behavioural characteristics in participants in the HARPdoc trial, which evaluates a novel intervention for treatment-resistant problematic hypoglycaemia. METHODS: We documented a cross-sectional baseline description of 99 adults with type 1 diabetes and problematic hypoglycaemia despite structured education in flexible insulin therapy. The following measures were included: Hypoglycaemia Fear Survey II (HFS-II); Attitudes to Awareness of Hypoglycaemia questionnaire (A2A); Hospital Anxiety and Depression Index; and Problem Areas In Diabetes. k-mean cluster analysis was applied to HFS-II and A2A factors. Data were compared with a peer group without problematic hypoglycaemia, propensity-matched for age, sex and diabetes duration (n = 81). RESULTS: The HARPdoc cohort had long-duration diabetes (mean ± SD 35.8 ± 15.4 years), mean ± SD Gold score 5.3 ± 1.2 and a median (IQR) of 5.0 (2.0-12.0) severe hypoglycaemia episodes in the previous year. Most individuals had been offered technology and 49.5% screened positive for anxiety (35.0% for depression and 31.3% for high diabetes distress). The cohort segregated into two clusters: in one (n = 68), people endorsed A2A cognitive barriers to hypoglycaemia avoidance, with low fear on HFS-II factors; in the other (n = 29), A2A factor scores were low and HFS-II high. Anxiety and depression scores were significantly lower in the comparator group. CONCLUSIONS/INTERPRETATION: The HARPdoc protocol successfully recruited people with treatment-resistant problematic hypoglycaemia. The participants had high anxiety and depression. Most of the cohort endorsed unhelpful health beliefs around hypoglycaemia, with low fear of hypoglycaemia, a combination that may contribute to persistence of problematic hypoglycaemia and may be a target for adjunctive psychological therapies.

Hypoglycemia Subtypes in Type 1 Diabetes: An Exploration of the Hypoglycemia Fear Survey-II.

OBJECTIVE: The Hypoglycemia Fear Survey-II (HFS-II) is a well-validated measure of fear of hypoglycemia in people with type 1 diabetes. The aim of this study was to explore the relationships between hypoglycemia worries, behaviors, and cognitive barriers to hypoglycemia avoidance and hypoglycemia awareness status, severe hypoglycemia, and HbA1c. RESEARCH DESIGN AND METHODS: Participants with type 1 diabetes (n = 178), with the study population enriched for people at risk for severe hypoglycemia (49%), completed questionnaires for assessing hypoglycemia fear (HFS-II), hyperglycemia avoidance (Hyperglycemia Avoidance Scale [HAS]), diabetes distress (Problem Areas In Diabetes [PAID]), and cognitive barriers to hypoglycemia avoidance (Attitudes to Awareness of Hypoglycemia [A2A]). Exploratory factor analysis was applied to the HFS-II. We sought to establish clusters based on HFS-II, A2A, Gold, HAS, and PAID using k-means clustering. RESULTS: Four HFS-II factors were identified: Sought Safety, Restricted Activity, Ran High, and Worry. While Sought Safety, Restricted Activity, and Worry increased with progressively impaired awareness and recurrent severe hypoglycemia, Ran High did not. With cluster analysis we outlined four clusters: two clusters with preserved hypoglycemia awareness were differentiated by low fear/low cognitive barriers to hypoglycemia avoidance (cluster 1) versus high fear and distress and increased Ran High behaviors (cluster 2). Two clusters with impaired hypoglycemia awareness were differentiated by low fear/high cognitive barriers (cluster 3) as well as high fear/low cognitive barriers (cluster 4). CONCLUSIONS: This is the first study to define clusters of hypoglycemia experience by worry, behaviors, and cognitive barriers to hypoglycemia avoidance. The resulting subtypes may be important in understanding and treating problematic hypoglycemia.

Autoantibody predictors of gastrointestinal symptoms in systemic sclerosis.

OBJECTIVES: To assess the prevalence and burden of SSc-related gastrointestinal dysfunction (SSc-GI) and to evaluate associations with demographic, clinical and serological characteristics. METHODS: Patients completed the UCLA SCTC GIT 2.0 questionnaire for SSc-GI disease to assess the burden of GI disease across multiple functional and psychological domains. Questionnaire scores were assessed using non-parametric and quantile regression analyses. RESULTS: Our cohort included 526 patients with SSc, with a typical distribution of disease-associated autoantibodies (ACA, ARA, ATA, PM-Scl, U1RNP, U3RNP). We demonstrated associations between hallmark antibodies and the domain-specific burden of GI disease. In particular, ACA, ARA and ENA-negative demonstrated increased SSc-GI disease burden, while PM-Scl conferred relative protection. In a distributional analysis, associations with autoantibodies were particularly marked in those with the highest burden of GI disease. CONCLUSION: There is a significant burden of SSc-GI disease in patients with SSc; reflux and bloating symptoms are most prominent. SSc hallmark antibodies may predict increased risk of SSc-GI disease, in particular ACA and ARA, while PM-Scl may be protective.