Updates of precision medicine in type 2 diabetes

Diabetes mellitus is prevalent worldwide and affects 1 in 10 adults. Despite the successful development of glucose-lowering drugs, such as glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 inhibitors recently, the proportion of patients achieving satisfactory glucose control has not risen as expected. The heterogeneity of diabetes determines that a one-size-fits-all strategy is not suitable for people with diabetes. Diabetes is undoubtedly more heterogeneous than the conventional subclassification, such as type 1, type 2, monogenic and gestational diabetes. The recent progress in genetics and epigenetics of diabetes has gradually unveiled the mechanisms underlying the heterogeneity of diabetes, and cluster analysis has shown promising results in the substratification of type 2 diabetes, which accounts for 95% of diabetic patients. More recently, the rapid development of sophisticated glucose monitoring and artificial intelligence technologies further enabled comprehensive consideration of the complex individual genetic and clinical information and might ultimately realize a precision diagnosis and treatment in diabetics.

Autologous Conditioned Serum in Lumbar and Cervical Radiculopathy: A Systemic Review

Background: Intervertebral disc degeneration causing radiculopathy is driven by catabolic cytokines like IL-1β and TNFα. Autologous conditioned serum (ACS) was found to be rich in IL-1Ra (Interleukin-1 Receptor Antagonist), and thus, can impede disc degeneration. A systematic review of available literature was conducted to ascertain the potential therapeutic application of ACS in radiculopathy. Methods: Systematic literature reviews were conducted in PubMed, Scopus and Embase databases, up to September 2020. Randomised controlled trials (RCTs), prospective, retrospective studies and case series with lumbar or cervical radiculopathy and reporting use of ACS were included, with at least one of the outcome measures like VAS (Visual Analogue Scale) for pain, SF-12 (Short Form of Health Survey-12), Oswestry Disability Index, with a minimum follow up of 3 months. Animal studies, s, review articles and case reports were excluded. Results: A total of four studies, including 107 patients who received ACS were included based on the eligibility criteria. Two were RCTs and two were prospective non-comparative studies. Three studies evaluated the effect of IL-1Ra on lumbar radiculopathy and one on cervical radiculopathy. The mean age of patients in the studies ranged from 37.15 to 53.9. The dose of ACS used was 2-4 mL injection. In 1 RCT, methylprednisolone was used as control, in the other 5 mg and 10 mg triamcinolone was used. All studies reported a statistically significant reduction in pre-injection and post-injection VAS, there was also a significant difference as compared to 5 mg triamcinolone. Three studies reported significant improvement in ODI. Two studies reported statistically significant improvement in SF-12 scores post injection (p < 0.001). For cervical radiculopathy, Neck pain disability score showed a decrease of 73.76% from pre-injection to final follow up and Neck disability index showed a decrease of 74.47%. Conclusion: All of the four studies concluded that epidural perineural injection with ACS, reduced pain scores (VAS, NPDS) and improved functional scores (ODI, SF-12 and NPDS), as compared to placebo and other conventional therapeutic modalities like steroids, and analgesic-anaesthetic-steroid cocktail. Hence, ACS is a promising new therapeutic modality in both lumbar and cervical radiculopathy, and further studies can strengthen the present evidence regarding its efficacy and safety profile. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Pandemic Highlights Urgency for New Methodologies for Evidence Generation

Randomized controlled trials, which many consider to be the gold standard of clinical research, were developed in the 1940s. [...]individual patients in the real world react often very differently to a specific drug than what has been predicted by the "mean" of a clinical trial. Many biopharmaceutical companies and AI startups are betting that with enough data, these methods will work so well that they will help to accelerate the discovery of new therapies for the novel corona virus, 2019-nCoV (see go.nature.com/3aLd0ll). * Causal AI methods might be uniquely positioned to discover underlying causes of disease and clinical response to treatment on an individual level, making personalized medicine real.

CLINICAL TRIAL INSIGHTS

With support from large databases, informatics, technologies, and advanced analytics we're able to target highly stratified patient subpopulations-eventually at the individual patient level- resulting in smaller and faster clinical trials, fewer adverse outcomes, greater likelihood of a treatment response, higher probability of approval, and lower overall development costs. Ultimately this second movement ensures that we are measuring outcomes that are the most clinically meaningful and relevant as defined by the community living with a given disease;and promises to deliver more feasible, faster clinical trials with better enrollment and retention rates, proportional representation according to disease prevalence by race and ethnicity and other individual characteristics, fewer unplanned and unbudgeted protocol amendments, higher approval rates, and accelerated commercialization. Research conducted by the Tufts Center for the Study of Drug Development and by others indicates that drug development failure rates are the highest they have ever been;the average overall duration of a development program and of a clinical trial by phase is not getting faster-they are taking longer and the durations are less predictable;recruitment and retention rates are at their lowest in history-particularly in oncology and rare diseases (two dominant segments of the R&D pipeline);the perennial 4% to 6% increase in overall R&D spending shows no sign of slowing;and we are observing higher levels of inefficiency and performance volatility.

Current Advances and Future Avenues in Endocrinology

Endocrinology is a dynamic science with numerous advances in the field of diagnosis, prognosis and management. Newer diagnostic modalities in the field have not only revolutionised the manner glycaemic status in diabetes is assessed but have provided newer metrics of evaluation, including ‘time in range' and the importance of glycaemic variability as an independent association with vascular complications. The focus on lifestyle management for weight and glycaemic optimisation is at an all-time high, especially in terms of time-restricted feeding, intermittent fasting and chrononutrition. Precision and personalised medicine is also foraying into mainstream endocrinology, with potential applications in diabetes mellitus as well as other disorders such as acromegaly and adrenal diseases (phaeochromocytoma/paraganglioma). Genetic testing for clinical and predictive endocrinology is another rapidly advancing domain with use in disease gene identification and discerning the genetic and molecular basis of various endocrine disorders. Avenues for the future implicate improved genetics, epigenetics and environmental factors to understand the intricacies of disease as well as design more effective therapeutic options. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

The Post-Pandemic CRO Landscape

None is inconsequential: advancing digital technology, globalization of clinical trials, changes in clinical trial design, the inflow of private equity dollars, fewer sponsors lost to mergers and acquisitions, more CROs, the costs of clinical trials, precision medicine, lack of available talent, and-an under the radar trend-the continuing challenges of chronic disease. A 2020 report called them a "primary factor" in the growth of global CRO services market.2 Casey McTigue, an executive director at SRS Acquiom, an M&A services firm, put it this way: "We have seen record setting volumes for M&A." Market attention In 2019, the life sciences recruiter Pr°Clinical considered the following CROs worthy of close attention from investors and pharma alike: PPD, Medpace, PRA Health Sciences, KCR, ICON, IQVIA, PSI, Parexel.3 Of the eight, three still stand alone;the rest have merged or been acquired. Combined, their network covers 2,800 hospitals, clinics and long-term care facilities, and 200 research and pharmaceutical companies, a press release says. Since the combined R&D outlay of the top pharma houses now hovers at the $100 billion-and that majority of trials have CRO involvement-even the math challenged can appreciate the CRO industry's losses, or gains, depending on the road chosen.6 But the CRO industry has already proved its resiliency. Despite changes in market conditions between 2008 and 2019, SRS Acquiom found that of the 227 private life sciences deals in which it was the shareholder representative, 163 had earnouts, the potential dollar figure more than $37 billion.

Prior Ambulatory Mild Coronavirus Disease 2019 Does Not Increase Risk of Acute Mountain Sickness.

Small, Elan, Caleb Phillips, William Bunzel, Lakota Cleaver, Nishant Joshi, Laurel Gardner, Rony Maharjan, and James Marvel. Prior ambulatory mild coronavirus disease 2019 does not increase risk of acute mountain sickness. High Alt Med Biol. 00:000-000, 2023. Background: Given its long-term morbidity, understanding how prior coronavirus disease 2019 (COVID-19) may affect acute mountain sickness (AMS) susceptibility is important for preascent risk stratification. The objective of this study was to examine if prior COVID-19 impacts risk of AMS. Materials and Methods: This was a prospective observational study conducted in Lobuje (4,940 m) and Manang (3,519 m), Nepal, from April to May 2022. AMS was defined by the 2018 Lake Louise Questionnaire criteria. COVID-19 severity was defined using the World Health Organization-developed criteria. Results: In the Lobuje cohort of 2,027, 46.2% of surveyed individuals reported history of COVID-19, with 25.7% AMS point-prevalence. There was no significant relationship between prior ambulatory mild COVID-19 and AMS (p = 0.6) or moderate AMS (p = 1.0). In the Manang cohort of 908, 42.8% reported history of COVID-19, with 14.7% AMS point-prevalence. There was no significant relationship between prior ambulatory mild COVID-19 and AMS (p = 0.3) or moderate AMS (p = 0.4). Average months since COVID-19 was 7.4 (interquartile range [IQR] 3-10) for Lobuje, 6.2 (IQR 3-6) for Manang. Both cohorts rarely exhibited moderate COVID-19 history. Conclusions: Prior ambulatory mild COVID-19 was not associated with increased risk of AMS and should not preclude high-altitude travel.

Bayesian Index Models for Heterogeneous Treatment Effects on a Binary Outcome.

This paper develops a Bayesian model with a flexible link function connecting a binary treatment response to a linear combination of covariates and a treatment indicator and the interaction between the two. Generalized linear models allowing data-driven link functions are often called "single-index models" and are among popular semi-parametric modeling methods. In this paper, we focus on modeling heterogeneous treatment effects, with the goal of developing a treatment benefit index (TBI) incorporating prior information from historical data. The model makes inference on a composite moderator of treatment effects, summarizing the effect of the predictors within a single variable through a linear projection of the predictors. This treatment benefit index can be useful for stratifying patients according to their predicted treatment benefit levels and can be especially useful for precision health applications. The proposed method is applied to a COVID-19 treatment study.

Pharmacogenetics-guided dalcetrapib therapy after an acute coronary syndrome: the dal-GenE trial.

AIMS: In a retrospective analysis of dal-Outcomes, the effect of dalcetrapib on cardiovascular events was influenced by an adenylate cyclase type 9 (ADCY9) gene polymorphism. The dal-GenE study was conducted to test this pharmacogenetic hypothesis. METHODS AND RESULTS: dal-GenE was a double-blind trial in patients with an acute coronary syndrome within 1-3 months and the AA genotype at variant rs1967309 in the ADCY9 gene. A total of 6147 patients were randomly assigned to receive dalcetrapib 600 mg or placebo daily. The primary endpoint was the time from randomization to first occurrence of cardiovascular death, resuscitated cardiac arrest, non-fatal myocardial infarction, or non-fatal stroke. After a median follow-up of 39.9 months, the primary endpoint occurred in 292 (9.5%) of 3071 patients in the dalcetrapib group and 327 (10.6%) of 3076 patients in the placebo group [hazard ratio 0.88; 95% confidence interval (CI) 0.75-1.03; P = 0.12]. The hazard ratios for the components of the primary endpoint were 0.79 (95% CI 0.65-0.96) for myocardial infarction, 0.92 (95% CI 0.64-1.33) for stroke, 1.21 (95% CI 0.91-1.60) for death from cardiovascular causes, and 2.33 (95% CI 0.60-9.02) for resuscitated cardiac arrest. In a pre-specified on-treatment sensitivity analysis, the primary endpoint event rate was 7.8% (236/3015) in the dalcetrapib group and 9.3% (282/3031) in the placebo group (hazard ratio 0.83; 95% CI 0.70-0.98). CONCLUSION: Dalcetrapib did not significantly reduce the risk of occurrence of the primary endpoint of ischaemic cardiovascular events at end of study. A new trial would be needed to test the pharmacogenetic hypothesis that dalcetrapib improves the prognosis of patients with the AA genotype. CLINICAL TRIAL REGISTRATION: Trial registration dal-GenE ClinicalTrials.gov Identifier: NCT02525939.

A Clinical Update on Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) traditionally refers to abnormal glucose tolerance with onset or first recognition during pregnancy. GDM has long been associated with obstetric and neonatal complications primarily relating to higher infant birthweight and is increasingly recognized as a risk factor for future maternal and offspring cardiometabolic disease. The prevalence of GDM continues to rise internationally due to epidemiological factors including the increase in background rates of obesity in women of reproductive age and rising maternal age and the implementation of the revised International Association of the Diabetes and Pregnancy Study Groups' criteria and diagnostic procedures for GDM. The current lack of international consensus for the diagnosis of GDM reflects its complex historical evolution and pragmatic antenatal resource considerations given GDM is now 1 of the most common complications of pregnancy. Regardless, the contemporary clinical approach to GDM should be informed not only by its short-term complications but also by its longer term prognosis. Recent data demonstrate the effect of early in utero exposure to maternal hyperglycemia, with evidence for fetal overgrowth present prior to the traditional diagnosis of GDM from 24 weeks' gestation, as well as the durable adverse impact of maternal hyperglycemia on child and adolescent metabolism. The major contribution of GDM to the global epidemic of intergenerational cardiometabolic disease highlights the importance of identifying GDM as an early risk factor for type 2 diabetes and cardiovascular disease, broadening the prevailing clinical approach to address longer term maternal and offspring complications following a diagnosis of GDM.

4 - Bayesian Statistical Methods in Stem Cell Transplantation and Cellular Therapy

A brief overview of Bayesian statistics is given, followed by illustrative applications of Bayesian methods in allogeneic hematopoietic cell transplantation (allo-HCT) and cellular therapy. Three clinical trial designs are described, including a study to evaluate safety and efficacy of cytotoxic T-lymphocytes for posttransplant viral infections, a trial to optimize chimeric antigen receptor T-cell dose for hematologic malignancies based on efficacy-toxicity trade-offs, and a randomized study of cord blood derived regulatory T-cells for COVID-19 induced acute respiratory distress syndrome. Three data analyses are described, including a sensitivity analysis of preparative regimen effects for allo-HCT that are confounded with institutional effects, regression-based estimation of the effects on survival of antigens in convalescent plasma therapy for COVID-19, and precision pharmacokinetic-guided dosing of intravenous busulfan in allo-HCT.

The need for integrated research autopsies in the era of precision oral medicine.

BACKGROUND: Autopsy has benefited the practice of medicine for centuries; however, its use to advance the practice of oral health care is relatively limited. In the era of precision oral medicine, the research autopsy is poised to play an important role in understanding oral-systemic health, including infectious disease, autoimmunity, craniofacial genetics, and cancer. TYPES OF STUDIES REVIEWED: The authors reviewed relevant articles that used medical and dental research autopsies to summarize the advantages of minimally invasive autopsies of dental, oral, and craniofacial tissues and to outline practices for supporting research autopsies of the oral and craniofacial complex. RESULTS: The authors provide a historical summary of research autopsy in dentistry and provide a perspective on the value of autopsies for high-resolution multiomic studies to benefit precision oral medicine. As the promise of high-resolution multiomics is being realized, there is a need to integrate the oral and craniofacial complex into the practice of autopsy in medicine. Furthermore, the collaboration of autopsy centers with researchers will accelerate the understanding of dental, oral, and craniofacial tissues as part of the whole body. CONCLUSIONS: Autopsies must integrate oral and craniofacial tissues as part of biobanking procedures. As new technologies allow for high-resolution, multimodal phenotyping of human samples, using optimized sampling procedures will allow for unprecedented understanding of common and rare dental, oral, and craniofacial diseases in the future. PRACTICAL IMPLICATIONS: The COVID-19 pandemic highlighted the oral cavity as a site for viral infection and transmission potential; this was only discovered via clinical autopsies. The realization of the integrated autopsy's value in full body health initiatives will benefit patients across the globe.

Trust and Willingness to Share Health Related Information: A quantitative study of Danish students' use of mHealth applications

mHealth technology has the potential to transform healthcare and realize the goal of precision medicine through systematic data collection and use. Meanwhile, mHealth applications developed during COVID-19 have had limited effect, as people have been reluctant to adopt them due to a lack of trust and willingness to share data. The aim of this empirical study is to provide insights into young people's use, trust, and willingness to share data through mHealth apps as future users of healthcare services. A survey comprising 484 Danish students was conducted. It focuses on mHealth app use, willingness to share data, and trust. The findings show that the trustworthiness of the technology and data requesting organization is important for establishing trust in mHealth apps. These insights indicate how young people can be motivated to trust mHealth apps, which can be used to develop future apps and exploit the untapped potential of the collected data. © 2023 IEEE Computer Society. All rights reserved.

Precision medicines in practice: the connection between CFTR modulators and deranged liver enzymes

Background and AimFor most of the 83 years since acknowledging cystic fibrosis (CF) as a separate disease entity, treatment has primarily focused on symptomatic relief.1 Following the discovery of the CFTR gene, efforts have been made to produce therapies to target the underlying dysfunctions caused by CFTR mutations.2 Moderate transaminase elevations are commonly observed in CF patients. Severe transaminase elevations have been observed in patients taking CFTR modulators in clinical trials with the initial STRIVE trial revealing that treatment discontinuation was commonly due to an increase in hepatic enzymes.3 Consequently, liver function test (LFTs) monitoring is recommended for all patients before commencing therapy, every three months for the first year and annually thereafter. This audit aims to assess the compliance of LFT monitoring in clinical practice for paediatric patients initiated on CFTR modulators, evaluate the incidence of liver-related adverse effects, and examine trends between the CFTR modulator used and the clinical significance of LFT derangements, and determine if there are any sex-related correlations.MethodsPatient data, including date and age on treatment initiation, gender, LFT results at baseline (AST, ALT, ALP, GGT and total bilirubin), first derangement since initiation and monitoring frequency were extracted from the clinical system Meditech®, pseudonymised and analysed. There were 91 records of patients being treated with a CFTR modulator. Some patients were on more than one CFTR modulator as treatment can be switched if eligible. For the purpose of the audit after consultation with the local CF clinical team, a two-month deviation outside of the recommended monitoring frequency was considered non-compliant. LFT derangements were classified as clinically significant if the result was higher than 3 times the upper limit of normal (ULN).ResultsOur study found that most patients (50/91 – 54.9%) on CFTR modulators in the tertiary centre did not have their LFTs monitored following the recommended guidelines. A statistically significant increase in LFT abnormalities from pre- to post- intervention with a CFTR modulator was observed (p=0.015). Kaftrio®/Kalydeco® (3/20 – 15%) and Orkambi® (1/29 – 3.4%) were the only CFTR modulators that led to patients developing clinically significant derangements (>3x ULN). Additionally, a greater proportion of females (24/51 – 47.1%) than males (15/40 – 37.5%) had abnormal LFTs within the tertiary centre contrary to previous epidemiological studies where males have been documented to have a greater risk of abnormal LFTs. However, the strength of this association was negligible (φ =0.096, p=0.360).ConclusionIn conclusion, the tertiary centre's compliance with LFT monitoring guidelines for patients initiated on CFTR modulators was substandard. Most records of treatment initiation occurred during COVID-19, which impacted monitoring as many hospitals suspended routine clinical work to limit the spread of the infection in high-risk groups. Time constraints limited the audit during the data extraction period;therefore, results should be interpreted cautiously. In the absence of the COVID-19 pandemic a re-audit process should include patient lifestyle data and consider other medication regimens that could potentially alter LFTs. Introducing a blood clerk would enable the CF unit to monitor LFT changes more efficiently.ReferencesGuimbellot J, Taylor-Cousar JL. Combination CFTR modulator therapy in children and adults with cystic fibrosis. The Lancet Respiratory Medicine 2021;9:677–679.Lopes-Pacheco M. CFTR Modulators: The Changing Face of Cystic Fibrosis in the Era of Precision Medicine. Frontiers of Pharmacology 2020;10:1662.Gavioli EM, Guardado N, Haniff F, et al. A current review of the safety of cystic fibrosis transmembrane conductance regulator modulators. Journal of Clinical Pharmacy and Therapeutics 2021;46:286–294.

Digital health technologies and major depressive disorder.

There is an urgent need to improve the clinical management of major depressive disorder (MDD), which has become increasingly prevalent over the past two decades. Several gaps and challenges in the awareness, detection, treatment, and monitoring of MDD remain to be addressed. Digital health technologies have demonstrated utility in relation to various health conditions, including MDD. Factors related to the COVID-19 pandemic have accelerated the development of telemedicine, mobile medical apps, and virtual reality apps and have continued to introduce new possibilities across mental health care. Growing access to and acceptance of digital health technologies present opportunities to expand the scope of care and to close gaps in the management of MDD. Digital health technology is rapidly evolving the options for nonclinical support and clinical care for patients with MDD. Iterative efforts to validate and optimize such digital health technologies, including digital therapeutics and digital biomarkers, continue to improve access to and quality of personalized detection, treatment, and monitoring of MDD. The aim of this review is to highlight the existing gaps and challenges in depression management and discuss the current and future landscape of digital health technology as it applies to the challenges faced by patients with MDD and their healthcare providers.

Harnessing Deep Learning for Omics in an Era of COVID-19.

Omics data are multidimensional, heterogeneous, and high throughput. Robust computational methods and machine learning (ML)-based models offer new prospects to accelerate the data-to-knowledge trajectory. Deep learning (DL) is a powerful subset of ML inspired by brain structure and has created unprecedented momentum in bioinformatics and computational biology research. This article provides an overview of the current DL models applied to multi-omics data for both the beginner and the expert user. Additionally, COVID-19 will continue to impact planetary health as a pandemic and an endemic disease, with genomic and multi-omic pathophysiology. DL offers, therefore, new ways of harnessing systems biology research on COVID-19 diagnostics and therapeutics. Herein, we discuss, first, the statistical ML algorithms and essential deep architectures. Then, we review DL applications in multi-omics data analysis and their intersection with COVID-19. Finally, challenges and several promising directions are highlighted going forward in the current era of COVID-19.

Redefying the therapeutic strategies against cardiorenal morbidity and mortality: Patient phenotypes.

Chronic kidney disease (CKD) patients face an unacceptably high morbidity and mortality, mainly from cardiovascular diseases. Diabetes mellitus, arterial hypertension and dyslipidemia are highly prevalent in CKD patients. Established therapeutic protocols for the treatment of diabetes mellitus, arterial hypertension, and dyslipidemia are not as effective in CKD patients as in the general population. The role of non-traditional risk factors (RF) has gained interest in the last decades. These entail the deranged clinical spectrum of secondary hyperparathyroidism involving vascular and valvular calcification, under the term "CKD-mineral and bone disorder" (CKD-MBD), uremia per se, inflammation and oxidative stress. Each one of these non-traditional RF have been addressed in various study designs, but the results do not exhibit any applied clinical benefit for CKD-patients. The "crusade" against cardiorenal morbidity and mortality in CKD-patients is in some instances, derailed. We propose a therapeutic paradigm advancing from isolated treatment targets, as practiced today, to precision medicine involving patient phenotypes with distinct underlying pathophysiology. In this regard we propose two steps, based on current stratification management of corona virus disease-19 and sepsis. First, select patients who are expected to have a high mortality, i.e., a prognostic enrichment. Second, select patients who are likely to respond to a specific therapy, i.e., a predictive enrichment.