Machine Learning Modeling from Omics Data as Prospective Tool for Improvement of Inflammatory Bowel Disease Diagnosis and Clinical Classifications

Research of inflammatory bowel disease (IBD) has identified numerous molecular players involved in the disease development. Even so, the understanding of IBD is incomplete, while disease treatment is still far from the precision medicine. Reliable diagnostic and prognostic biomarkers in IBD are limited which may reduce efficient therapeutic outcomes. High-throughput technologies and artificial intelligence emerged as powerful tools in search of unrevealed molecular patterns that could give important insights into IBD pathogenesis and help to address unmet clinical needs. Machine learning, a subtype of artificial intelligence, uses complex mathematical algorithms to learn from existing data in order to predict future outcomes. The scientific community has been increasingly employing machine learning for the prediction of IBD outcomes from comprehensive patient data-clinical records, genomic, transcriptomic, proteomic, metagenomic, and other IBD relevant omics data. This review aims to present fundamental principles behind machine learning modeling and its current application in IBD research with the focus on studies that explored genomic and transcriptomic data. We described different strategies used for dealing with omics data and outlined the best-performing methods. Before being translated into clinical settings, the developed machine learning models should be tested in independent prospective studies as well as randomized controlled trials

Falsifiable Network Models. A Network-based Approach to Predict Treatment Efficacy in Ulcerative Colitis

This work is focused on understanding the treatment efficacy of patients with ulcerative colitis (UC) using a network-based approach. UC is one of two forms of inflammatory bowel disease (IBD) along with Crohn’s disease. UC is a debilitating condition characterized by chronic inflammation and ulceration of the colon and rectum. UC symptoms occur gradually rather than abruptly, and the degree of symptoms differs across UC patients. Only around 20% of all UC cases can be explained by known genetic variations, implying a more ambiguous aetiology that is yet not fully understood but is thought to involve a complex interplay between genetic and environmental factors. The available therapy for UC substantially reduces symptoms and achieves long-term remission. However, about one-third of UC patients fail to respond to anti-TNFα therapy and consequently develop long-term side effects due to medication. Non-response to existing antibody-based therapies in subgroups of UC patients is a major challenge and incurs a healthcare burden. Therefore, the disease markers for predicting therapy response to assist individualized therapy decisions are needed. To date, no quantitative computational framework is available to predict treatment response in UC. We developed a quantitative framework that uses gene expression data and existing biological background information on signalling pathways to quantify network connectivity from receptors to transcription factors (TF) that are involved in UC pathogenesis. Variations in network connectivity in UC patients can be used to identify responders and non-responders to anti-TNFα and anti-Integrin treatment. Our findings allow us to summarize the effect of small gene expression changes on the overall connectivity of a signalling network and estimate the effect this will have on the individual patients' responses. Estimating the network connectivity associated with varied drug responses may provide an understanding of individualized treatment outcomes. Our model could be used to generate testable hypotheses about how individual genes act together in networks to cause inflammation in UC as well as other immune-inflammatory diseases such as psoriasis, asthma, and rheumatoid arthritis

MOLECULAR STRATIFICATION AND PROGNOSTIC DETERMINANTS OF ADULT AND PEDIATRIC CROHN’S DISEASE

Benjamin P. Keith: Molecular stratification and prognostic determinants of adult and pediatric Crohn’s disease (Under the direction of Terry Furey, Praveen Sethupathy, and Shehzad Sheikh) Crohn’s disease (CD) is a chronic relapsing gastrointestinal inflammatory disorder with heterogeneous clinical presentation. Current clinical diagnostic methods involve invasive procedures and are ineffective towards predicting disease progression and response to therapy. High-throughput sequencing technologies have been utilized in various complex disorders to identify disease subtypes based on molecular signatures that are associated with clinical parameters. Given the success of molecular subtyping, particularly within the cancer field, there is substantive interest in implementing this methodology to predict disease progression and treatment response in CD. By analyzing differences in colonic gene expression between CD patients, our group revealed 2 subsets of patients—a group characterized by genes more highly expressed in the colon (colon-like CD) and a group with increased expression of ileum marker genes (ileum-like CD). Building on these initial findings, we aimed to validate molecular subtypes associated with CD through analysis of RNA-sequencing and small RNA-sequencing data in adult and pediatric cohorts. In the following chapters, I show that CD molecular subtypes can be detected using genome-wide expression of microRNAs, a class of small non-coding RNAs that post-transcriptionally regulate gene expression. Further, I show that microRNA-31 (miR-31) is a molecular driver of CD subtypes in both adult and pediatric patient cohorts and, through association analyses of clinical patient phenotypes, show that miR-31 expression levels are associated with the development of distinct disease outcomes. Using gene expression data from a large cohort of adult colon-like patients, I identified heterogeneous expression signatures that suggests an additional molecular subtype of CD associated with the expression of Paneth cell markers. Together, the results presented in the dissertation provide novel insights into the molecular heterogeneity of CD that can be used to guide future molecular subtyping research within the field by our group and the wider IBD research communityDoctor of Philosoph

The impact of acute oral sodium propionate supplementation on energy metabolism

Background: Previous research has demonstrated that acute propionate supplementation in humans can have favourable effects on energy metabolism by raising energy expenditure and lipid oxidation. Moreover, acute propionate supplementation in humans has shown to affect subjective appetite by increasing nausea and triggering the release of the anorectic hormone glucagon-like peptide 1 (GLP-1). Studies investigating the acute effects of propionate administration on glucose homeostasis in humans report conflicting outcomes. However, previous research has generally only investigated the acute impact of propionate supplementation in the overnight fasted state and for relatively short observation periods (<180 min).It is, therefore, presently unknown how raised bioavailability of gut-derived propionate modulates energy metabolism during physical activity and in the postprandial state. Consequently, the aim of the present trial is to investigate the acute effect of sodium propionate supplementation on energy expenditure, substrate oxidation, appetite response and glucose homeostasis in three different energy states (overnight fasted, sub-maximal exercise and post-prandial) and over longer time-periods. Moreover, NMR (nuclear magnetic resonance) spectroscopy was used to investigate changes in serum metabolite phenotype after sodium propionate ingestion. Methodology: The thesis is comprised of three separate randomized controlled double-blind cross-over studies (overnight fasted, submaximal exercise, and postprandial). In each study, following an overnight fast, tablets containing either sodium propionate or sodium chloride (Control) were first administered over 180 min. Overnight Fasted study: 19 volunteers (11 males and 8 females; age: 34.6 4.1 years; BMI (body mass index): 23.1 0.7 kg/m2) completed the two study visits after an overnight fast. The study extended over a total period of 360 min while volunteers remained fasted for the duration of the study. Sub-maximal exercise study: 19 volunteers (14 males and 5 females; age: 42.7 3.5 years; BMI: 24.5 0.7 kg/m2) completed a maximal exercise test visit and two study visits. The study extended over a total period of 240 min. At time-point 180 min, participants exercised at 40% of VO2 max for 60 min. Post-prandial study: 19 volunteers (12 males and 7 females; age: 45.0 3.5 years; BMI: 24.8 0.8 kg/m2) completed two study visits. The study extended over a total period of 300 min. At time-point 180 min, a mixed calorie liquid meal (Ensure Original Vanilla Nutrition Shake: 72.7 g carbohydrate, 13.6 g fat and 20.5 g protein; 500 kcal) was provided to volunteers. Energy expenditure and substrate oxidation were measured throughout these visits using indirect calorimetry. Participants were asked to complete 100mm visual analogue scales (VAS) that assessed subjective appetite (hunger, thirst and nausea) throughout these visits. Insulin resistance and insulin sensitivity were assessed via HOMA-IR and Matsuda Index respectively. The oral disposition index (ODI) was used to assess β-cell function. In the post-prandial trial, GLP-1 release was measured, and 1H-NMR spectroscopy was used to analyse serum metabolite profile associated with propionate supplementation. Results: Propionate supplementation increased energy expenditure in the overnight fasted state, which was mainly observed within the first 180 min of ingestion, and in the post-prandial state. A consistent increase in lipid oxidation was found in the overnight fasted state, however, these effects were not observed during submaximal exercise or in the post-prandial state. A decrease in carbohydrate (CHO) oxidation was also found in the overnight fasted state. Propionate ingestion increased subjective nausea in the overnight fasted and post-prandial states and increased subjective thirst during submaximal exercise. However, no effect on subjective hunger was found was found in the three different energy states. GLP-1 secretion was significantly increased in the overnight fasted state, however, insulin sensitivity and β-cell function were unaffected with propionate ingestion. In the overnight fasted state, low density lipoprotein (LDL)/ very low-density lipoprotein (VLDL), lactate and methanol were upregulated and 3-hydroxybutyrate and lysine were supressed following propionate supplementation. LDL/VLDL, lactate and alanine were upregulated following propionate supplementation in the postprandial state. Conclusion: This thesis is the first to demonstrate that acute oral sodium propionate supplementation in healthy human volunteers can have favourable effects on energy metabolism in different energy states. Should these effects be replicated over longer time periods would suggest that increasing systemic levels of gut-derived propionate appears would be a promising strategy to improve long term energy balance and body weight management.Open Acces

Timely and reliable evaluation of the effects of interventions: a framework for adaptive meta-analysis (FAME)

Most systematic reviews are retrospective and use aggregate data AD) from publications, meaning they can be unreliable, lag behind therapeutic developments and fail to influence ongoing or new trials. Commonly, the potential influence of unpublished or ongoing trials is overlooked when interpreting results, or determining the value of updating the meta-analysis or need to collect individual participant data (IPD). Therefore, we developed a Framework for Adaptive Metaanalysis (FAME) to determine prospectively the earliest opportunity for reliable AD meta-analysis. We illustrate FAME using two systematic reviews in men with metastatic (M1) and non-metastatic (M0)hormone-sensitive prostate cancer (HSPC)

Effects of Diversity and Neuropsychological Performance in an NFL Cohort

Objective: The aim of this study was to examine the effect of ethnicity on neuropsychological test performance by comparing scores of white and black former NFL athletes on each subtest of the WMS. Participants and Methods: Data was derived from a de-identified database in South Florida consisting of 63 former NFL white (n=28, 44.4%) and black (n=35, 55.6%) athletes (Mage= 50.38; SD= 11.57). Participants completed the following subtests of the WMS: Logical Memory I and II, Verbal Paired Associates I and II, and Visual Reproduction I and II. Results: A One-Way ANOVA yielded significant effect between ethnicity and performance on several subtests from the WMS-IV. Black athletes had significantly lower scores compared to white athletes on Logical Memory II: F(1,61) = 4.667, p= .035, Verbal Paired Associates I: F(1,61) = 4.536, p = .037, Verbal Paired Associates: II F(1,61) = 4.677, p = .034, and Visual Reproduction I: F(1,61) = 6.562, p = .013. Conclusions: Results suggest significant differences exist between white and black athletes on neuropsychological test performance, necessitating the need for proper normative samples for each ethnic group. It is possible the differences found can be explained by the psychometric properties of the assessment and possibility of a non-representative sample for minorities, or simply individual differences. Previous literature has found white individuals to outperform African-Americans on verbal and non-verbal cognitive tasks after controlling for socioeconomic and other demographic variables (Manly & Jacobs, 2002). This highlights the need for future investigators to identify cultural factors and evaluate how ethnicity specifically plays a role on neuropsychological test performance. Notably, differences between ethnic groups can have significant implications when evaluating a sample of former athletes for cognitive impairment, as these results suggest retired NFL minorities may be more impaired compared to retired NFL white athletes

Distinguishing Performance on Tests of Executive Functions Between Those with Depression and Anxiety

Objective: To see if there are differences in executive functions between those diagnosed with Major Depressive Disorder (MDD) and those with Generalized Anxiety Disorder (GAD).Participants and Methods: The data were chosen from a de-identified database at a neuropsychological clinic in South Florida. The sample used was adults diagnosed with MDD (n=75) and GAD (n=71) and who had taken the Halstead Category Test, Trail Making Test, Stroop Test, and the Wisconsin Card Sorting Test. Age (M=32.97, SD=11.75), gender (56.7% female), and race (52.7% White) did not differ between groups. IQ did not differ but education did (MDD=13.41 years, SD=2.45; GAD=15.11 years, SD=2.40), so it was ran as a covariate in the analyses. Six ANCOVAs were run separately with diagnosis being held as the fixed factor and executive function test scores held as dependent variables. Results: The MDD group only performed worse on the Category Test than the GAD group ([1,132]=4.022, p\u3c .05). Even though both WCST scores used were significantly different between the two groups, both analyses failed Levene’s test of Equality of Error Variances, so the data were not interpreted. Conclusions: Due to previous findings that those diagnosed with MDD perform worse on tests of executive function than normal controls (Veiel, 1997), this study wanted to compare executive function performance between those diagnosed with MDD and those with another common psychological disorder. The fact that these two groups only differed on the Category Test shows that there may not be much of a difference in executive function deficits between those with MDD and GAD. That being said, not being able to interpret the scores on the WCST test due to a lack of homogeneity of variance indicates that a larger sample size is needed to compare these two types of patients, as significant differences may be found. The results of this specific study, however, could mean that the Category Test could be used in assisting the diagnosis of a MDD patient

The Effect of Ethnicity on Neuropsychological Test Performance of Former NFL Athletes

Objective: To investigate the effect of ethnicity on neuropsychological test performance by specifically exploring differences between white and black former NFL athletes on subtests of the WAIS-IV. Participants and Methods: Data was derived from a de-identified database in Florida consisting of 63 former NFL athletes (Mage=50.38; SD=11.57); 28 white and 35 black. Participants completed the following subtests of the WAIS-IV: Block Design, Similarities, Digit Span, Matrix Reasoning, Arithmetic, Symbol Search, Visual Puzzles, Coding, and Cancellation. Results: One-Way ANOVA yielded a significant effect between ethnicity and performance on several subtests. Black athletes had significantly lower scaled scores than white athletes on Block Design F(1,61)=14.266, p\u3c.001, Similarities F(1,61)=5.904, p=.018, Digit Span F(1,61)=8.985, p=.004, Arithmetic F(1,61)=16.07, p\u3c.001 and Visual Puzzles F(1,61)=16.682, p\u3c .001. No effect of ethnicity was seen on performance of Matrix Reasoning F(1,61)=2.937, p=.092, Symbol Search F(1,61)=3.619, p=.062, Coding F(1,61)=3.032, p=.087 or Cancellation F(1,61)=2.289, p=.136. Conclusions: Results reveal significant differences between white and black athletes on all subtests of the WAIS-IV but those from the Processing Speed Scale and Matrix Reasoning. These findings align with previous literature that found white individuals to outperform African-Americans on verbal and non-verbal tasks after controlling for socioeconomic and demographic variables (Manly & Jacobs, 2002). These differences may also be a reflection of the WAIS-IV’s psychometric properties and it is significant to consider the normative sample used may not be appropriate for African-Americans. This study highlights the need for future research to identify how ethnicity specifically influences performance, sheds light on the importance of considering cultural factors when interpreting test results, and serves as a call to action to further understand how and why minorities may not be accurately represented in neuropsychological testing

Regional Cerebral Blood Flow Patterns in Children vs. Adults with ADHD Combined and Inattentive Types: A SPECT Study

Objective: The current study sought to determine whether ADHD Combined Type (ADHD-C) and ADHD Primarily Inattentive Type (ADHD-PI) showed differential regional cerebral blood flow (rCBF) patterns in children vs. adults. Participants and Methods: The overall sample (N=1484) was effectively split into four groups: adults with ADHD-PI (n=519), adults with ADHD-C (n=405), children with ADHD-PI (n=192), children with ADHD-C (n=368). All participants were void of bipolar, schizophrenia, autism, neurocognitive disorders, and TBI. The data were collected from a de-identified archival database of individuals who underwent SPECT scans at rest. Results: Using αConclusions: Overall, the current study suggested that children may show rCBF differences between different ADHD subtypes, but adults may not. The current study did not find significance in any of the 17 brain regions examined when comparing adults with ADHD-C to adults with ADHD-PI. All significant findings were attributed to the children with ADHD-C group showing aberrant blood flow rate than at least one other group. Previous research has supported that the differentiation of these subtypes as distinctive disorders is difficult to make in adults (Sobanski et al., 2006). Other research has indicated the potential of imaging techniques to differentiate the two in children (Al-Amin, Zinchenko, & Geyer, 2018). The current findings support nuanced ways in which rCBF patterns of ADHD-C and ADHD-PI differ between children and adults

Advances in Autism Research

This book represents one of the most up-to-date collections of articles on clinical practice and research in the field of Autism Spectrum Disorders (ASD). The scholars who contributed to this book are experts in their field, carrying out cutting edge research in prestigious institutes worldwide (e.g., Harvard Medical School, University of California, MIND Institute, King’s College, Karolinska Institute, and many others). The book addressed many topics, including (1) The COVID-19 pandemic; (2) Epidemiology and prevalence; (3) Screening and early behavioral markers; (4) Diagnostic and phenotypic profile; (5) Treatment and intervention; (6) Etiopathogenesis (biomarkers, biology, and genetic, epigenetic, and risk factors); (7) Comorbidity; (8) Adulthood; and (9) Broader Autism Phenotype (BAP). This book testifies to the complexity of performing research in the field of ASD. The published contributions underline areas of progress and ongoing challenges in which more certain data is expected in the coming years. It would be desirable that experts, clinicians, researchers, and trainees could have the opportunity to read this updated text describing the challenging heterogeneity of Autism Spectrum Disorder