Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Gene expression profiles during thyroid embryonic development

Congenital Hypothyroidism (CH) is commonly due to structural defects of thyroid gland, collectively known as thyroid dysgenesis. Defects in growth and/or differentiation of the thyroid primordium can result in an absent (athyreosis) or hypoplastic thyroid; an impaired migration of thyroid precursor cells causes an ectopic gland (Van Vliet G, 2003). The clinical picture of thyroid dysgenesis thus suggests that defects of the specification, survival and movement of thyroid precursor cells are the key aberrations in CH. Understanding the regulation of early thyroid morphogenesis is thus important to elucidate the pathogenesis of CH. Murine models with target inactivation of the transcription factors Nkx2.1, Pax8, Foxe1 and Hhex expressed in thyroid progenitor cells and in the adult gland have demonstrated their important functions in thyroid development (De Felice M and Di Lauro R, 2004). Even though the thyroid is specified in each of these models it later disappears suggesting a role of these transcription factors also in the survival and expansion of the thyroid progenitors cell population. However, very few germ-line mutations have been detected in the corresponding genes of human patients with thyroid dysgenesis (Al Taji et al., 2007) suggesting the importance of additional genes. The aim of this thesis has been to discovery these genes by an unbiased search for transcripts enriched in the early thyroid primordium. Mouse thyroid primordia at the bud stage (E10.5) were isolated by laser capture microdissection (LCM). In parallel, RNA from whole embryos was obtained. RNA was amplified and labelled; samples were hybridized to Affymetrix microarrays. Bioinformatic analysis tools identified over 3000 transcripts as significantly enriched in the thyroid bud as compared to expression in the whole embryo. Such an enrichment is expressed as Fold Change (FC), 450 transcripts out 3000 displayed a FC >5. High and restricted expression of several of these in the E10.5 thyroid bud was confirmed experimentally by in situ hybridization on mouse embryos. This preliminary analysis indicates that the list has a high degree of validity. By this approach I have identified a large number of transcripts enriched in the embryonic thyroid bud with currently unknown functions in its development. This list will be an important resource in further efforts to elucidate the genetic networks that govern thyroid morphogenesis and might underlie CH

Adipose Tissue Dysfunction as Determinant of Obesity-Associated Metabolic Complications

Obesity is a critical risk factor for the development of type 2 diabetes (T2D), and its prevalence is rising worldwide. White adipose tissue (WAT) has a crucial role in regulating systemic energy homeostasis. Adipose tissue expands by a combination of an increase in adipocyte size (hypertrophy) and number (hyperplasia). The recruitment and differentiation of adipose precursor cells in the subcutaneous adipose tissue (SAT), rather than merely inflating the cells, would be protective from the obesity-associated metabolic complications. In metabolically unhealthy obesity, the storage capacity of SAT, the largest WAT depot, is limited, and further caloric overload leads to the fat accumulation in ectopic tissues (e.g., liver, skeletal muscle, and heart) and in the visceral adipose depots, an event commonly defined as “lipotoxicity.„ Excessive ectopic lipid accumulation leads to local inflammation and insulin resistance (IR). Indeed, overnutrition triggers uncontrolled inflammatory responses in WAT, leading to chronic low-grade inflammation, therefore fostering the progression of IR. This review summarizes the current knowledge on WAT dysfunction in obesity and its associated metabolic abnormalities, such as IR. A better understanding of the mechanisms regulating adipose tissue expansion in obesity is required for the development of future therapeutic approaches in obesity-associated metabolic complications

An essential role for Pax8 in the transcriptional regulation of Cadherin-16 in thyroid cells.

Cadherin-16 was originally identified as a tissue-specific cadherin present exclusively in kidney. Only recently, Cadherin-16 has been detected also on the plasma membrane of mouse thyrocytes. This last finding prompted us to note that the expression profile of Cadherin-16 resembles that of the transcription factor Pax8, a member of the Pax (paired-box) gene family, predominantly expressed in the developing and adult kidney and thyroid. Pax8 has been extensively characterized in the thyroid and shown to be a master gene for thyroid development and differentiation. In this study, we determined the role of the transcription factor Pax8 in the regulation of Cadherin-16 expression. We demonstrate that the Cadherin-16 minimal promoter is transcriptionally active in thyroid cells as well as in kidney cells, that Pax8 is able to activate transcription from a Cadherin-16 promoter reporter construct, and more importantly, that indeed Pax8 is able to bind in vivo the Cadherin-16 promoter region. In addition, by means of Pax8 RNA interference in thyroid cells and by analyzing Pax8 null mice, we demonstrate that Pax8 regulates also in vivo the expression of Cadherin-16. Finally, we reveal that the expression of Cadherin-16 is TSH dependent in FRTL-5 thyroid cells and significantly reduced in mouse thyroid carcinomas. Therefore, we conclude that Cadherin-16 is a novel downstream target of the transcription factor Pax8, likely since the early steps of thyroid development, and that its expression is associated with the fully differentiated state of the thyroid cell

Nutritional Factors, DNA Methylation, and Risk of Type 2 Diabetes and Obesity: Perspectives and Challenges

A healthy diet improves life expectancy and helps to prevent common chronic diseases such as type 2 diabetes (T2D) and obesity. The mechanisms driving these effects are not fully understood, but are likely to involve epigenetics. Epigenetic mechanisms control gene expression, maintaining the DNA sequence, and therefore the full genomic information inherited from our parents, unchanged. An interesting feature of epigenetic changes lies in their dynamic nature and reversibility. Accordingly, they are susceptible to correction through targeted interventions. Here we will review the evidence supporting a role for nutritional factors in mediating metabolic disease risk through DNA methylation changes. Special emphasis will be placed on the potential of using DNA methylation traits as biomarkers to predict risk of obesity and T2D as well as on their response to dietary and pharmacological (epi-drug) interventions

Epigenetic Reprogramming of the Inflammatory Response in Obesity and Type 2 Diabetes

For the past several decades, the prevalence of obesity and type 2 diabetes (T2D) has continued to rise on a global level. The risk contributing to this pandemic implicates both genetic and environmental factors, which are functionally integrated by epigenetic mechanisms. While these conditions are accompanied by major abnormalities in fuel metabolism, evidence indicates that altered immune cell functions also play an important role in shaping of obesity and T2D phenotypes. Interestingly, these events have been shown to be determined by epigenetic mechanisms. Consistently, recent epigenome-wide association studies have demonstrated that immune cells from obese and T2D individuals feature specific epigenetic profiles when compared to those from healthy subjects. In this work, we have reviewed recent literature reporting epigenetic changes affecting the immune cell phenotype and function in obesity and T2D. We will further discuss therapeutic strategies targeting epigenetic marks for treating obesity and T2D-associated inflammation

State-Dependent Aberrant Gamma-Aminobutyric Acid Reactivity and Downstream Functional Connectivity of Central Autonomic Network Subserve Pathological Intrusive Thinking

Alterations in neurotransmission mediated by gamma-aminobutyric acid (GABA), the main inhibitory neurotransmitter, are posited to play a pathophysiological role in stress-related disorders. Evidence, however, comes from the comparisons of pathological and healthy samples at rest and not during specic disease states, making it dicult to understand the processes underlying this assumption. The present study used 3T-proton magnetic resonance spectroscopy to investigate the effects of an experimental induction of intrusive thinking (IT; a transdiagnostic psychiatric symptom) on GABAergic and glutamatergic neurometabolic concentration within the bilateral Anterior Cingulate Cortex (ACC) in individuals with a pathological tendency to engage in IT (n = 29; 11 males) and controls (n = 29; 16 males). To assess physiological and functional concomitants of these neurochemical changes, autonomic measures and resting-state functional magnetic resonance imaging were also acquired before and after induction of IT. While engendering levels of IT amplied ACC GABA and GABA to Glx in the pathological group, an opposite trend emerged for controls. Notably, the pre-to post induction increase in GABAergic neurometabolism in the pathological group was accompanied by a dampened autonomic and resting state functional connectivity within nodes of the Central Autonomic Network. Current results are in line with the view of IT as a “better safe than sorry” strategy, which may be maintained in pathological conditions via a negative reinforcement mechanism through which increased GABAergic neurotransmission fosters avoidance of the transition from a relaxed state to a sudden spike of autonomic activation

Increased hexosamine biosynthetic pathway flux dedifferentiates INS-1E cells and murine islets by an extracellular signal-regulated kinase (ERK)1/2-mediated signal transmission pathway

Beta cell failure is caused by loss of cell mass, mostly by apoptosis, but also by simple dysfunction (decline of glucose-stimulated insulin secretion, downregulation of specific gene expression). Apoptosis and dysfunction are caused, at least in part, by lipoglucotoxicity. The mechanisms implicated are oxidative stress, increase in the hexosamine biosynthetic pathway (HBP) flux and endoplasmic reticulum (ER) stress. Oxidative stress plays a role in glucotoxicity-induced beta cell dedifferentiation, while glucotoxicity-induced ER stress has been mostly linked to beta cell apoptosis. We sought to clarify whether ER stress caused by increased HBP flux participates in a dedifferentiating response of beta cells, in the absence of relevant apoptosis

The Transcription Factor <i>HOXA5</i>: Novel Insights into Metabolic Diseases and Adipose Tissue Dysfunction

The transcription factor HOXA5, from the HOX gene family, has long been studied due to its critical role in physiological activities in normal cells, such as organ development and body patterning, and pathological activities in cancer cells. Nonetheless, recent evidence supports the hypothesis of a role for HOXA5 in metabolic diseases, particularly in obesity and type 2 diabetes (T2D). In line with the current opinion that adipocyte and adipose tissue (AT) dysfunction belong to the group of primary defects in obesity, linking this condition to an increased risk of insulin resistance (IR) and T2D, the HOXA5 gene has been shown to regulate adipocyte function and AT remodeling both in humans and mice. Epigenetics adds complexity to HOXA5 gene regulation in metabolic diseases. Indeed, epigenetic mechanisms, specifically DNA methylation, influence the dynamic HOXA5 expression profile. In human AT, the DNA methylation profile at the HOXA5 gene is associated with hypertrophic obesity and an increased risk of developing T2D. Thus, an inappropriate HOXA5 gene expression may be a mechanism causing or maintaining an impaired AT function in obesity and potentially linking obesity to its associated disorders. In this review, we integrate the current evidence about the involvement of HOXA5 in regulating AT function, as well as its association with the pathogenesis of obesity and T2D. We also summarize the current knowledge on the role of DNA methylation in controlling HOXA5 expression. Moreover, considering the susceptibility of epigenetic changes to reversal through targeted interventions, we discuss the potential therapeutic value of targeting HOXA5 DNA methylation changes in the treatment of metabolic diseases

Synthetic Post-Contrast Imaging through Artificial Intelligence: Clinical Applications of Virtual and Augmented Contrast Media

Contrast media are widely diffused in biomedical imaging, due to their relevance in the diagnosis of numerous disorders. However, the risk of adverse reactions, the concern of potential damage to sensitive organs, and the recently described brain deposition of gadolinium salts, limit the use of contrast media in clinical practice. In recent years, the application of artificial intelligence (AI) techniques to biomedical imaging has led to the development of ‘virtual’ and ‘augmented’ contrasts. The idea behind these applications is to generate synthetic post-contrast images through AI computational modeling starting from the information available on other images acquired during the same scan. In these AI models, non-contrast images (virtual contrast) or low-dose post-contrast images (augmented contrast) are used as input data to generate synthetic post-contrast images, which are often undistinguishable from the native ones. In this review, we discuss the most recent advances of AI applications to biomedical imaging relative to synthetic contrast media