Addressing the needs of traumatic brain injury with clinical proteomics.

BackgroundNeurotrauma or injuries to the central nervous system (CNS) are a serious public health problem worldwide. Approximately 75% of all traumatic brain injuries (TBIs) are concussions or other mild TBI (mTBI) forms. Evaluation of concussion injury today is limited to an assessment of behavioral symptoms, often with delay and subject to motivation. Hence, there is an urgent need for an accurate chemical measure in biofluids to serve as a diagnostic tool for invisible brain wounds, to monitor severe patient trajectories, and to predict survival chances. Although a number of neurotrauma marker candidates have been reported, the broad spectrum of TBI limits the significance of small cohort studies. Specificity and sensitivity issues compound the development of a conclusive diagnostic assay, especially for concussion patients. Thus, the neurotrauma field currently has no diagnostic biofluid test in clinical use.ContentWe discuss the challenges of discovering new and validating identified neurotrauma marker candidates using proteomics-based strategies, including targeting, selection strategies and the application of mass spectrometry (MS) technologies and their potential impact to the neurotrauma field.SummaryMany studies use TBI marker candidates based on literature reports, yet progress in genomics and proteomics have started to provide neurotrauma protein profiles. Choosing meaningful marker candidates from such 'long lists' is still pending, as only few can be taken through the process of preclinical verification and large scale translational validation. Quantitative mass spectrometry targeting specific molecules rather than random sampling of the whole proteome, e.g., multiple reaction monitoring (MRM), offers an efficient and effective means to multiplex the measurement of several candidates in patient samples, thereby omitting the need for antibodies prior to clinical assay design. Sample preparation challenges specific to TBI are addressed. A tailored selection strategy combined with a multiplex screening approach is helping to arrive at diagnostically suitable candidates for clinical assay development. A surrogate marker test will be instrumental for critical decisions of TBI patient care and protection of concussion victims from repeated exposures that could result in lasting neurological deficits

Novel serum biomarkers and their association with measured and estimated GFR decline in the general population

Chronic kidney disease (CKD) is an increasing health problem globally, now affecting 8-13% of the world’s population. The prevalence of CKD increases dramatically with age because kidney function, as assessed by the glomerular filtration rate (GFR), declines with age. The rate of GFR loss varies significantly between individuals regardless of known risk factors. However, current kidney biomarkers are suboptimal at predicting those at high risk of accelerated glomerular filtration rate (GFR) decline, especially when GFR is >60 ml/min/1.73m2. Thus, there is an unmet need to identify high-risk individuals or groups of people for early measures to delay or prevent CKD development. This thesis explores the relationship between baseline levels of 18 serum biomarkers and GFR decline over 5.6 and 11.0 years of follow-up in 1627 individuals in a healthy general middle-aged population, without cardiovascular disease, kidney disease, or diabetes at baseline. The GFR was measured (mGFR) using iohexol clearance at baseline and follow-up. We also investigated whether there are discrepancies in the relationship between the biomarkers and GFR decline when using the measured GFR or the commonly used estimated GFR (eGFR) from creatinine or cystatin C. Only one biomarker (MMP7) was independently associated with GFR decline independent of follow-up time, estimated or measured GFR, or how GFR decline was defined. MMP7 also predicted incident CKD and accelerated GFR decline beyond traditional CKD risk factors. Associations between the other proteins and GFR decline varied depending on whether the GFR was estimated or measured using iohexol. Thus, for some biomarkers, associations with eGFR decline may not be reproducible with mGFR. Results from studies on biomarkers for GFR decline, using eGFR and particularly eGFR from cystatin C, should be interpreted with caution

Establishing Biological Plausibility for Cognitive Frailty

Cognitive frailty is considered a potentially reversible age-related condition characterized by the simultaneous presence of both physical frailty and cognitive decline. The concept of cognitive frailty existing in older adults is indisputable, although the mechanisms and the directional relationship behind the dynamic association remain unexplained. Mechanisms have been suggested, often linking cognitive frailty to cognitive impairment or as a component of frailty but without an understanding of the biological bases for these associations we cannot not move forward with intervention trials. This dissertation examines the biological mechanisms for cognitive frailty. The study is the first to use a large number of protein and genetic markers identified by a systematic review to define the underlying pathology for cognitive frailty. We use an innovative Boosted trees machine learning technique for developing a population based predictive model. Xgboost is based in boosted trees and provides more efficient and accurate predictive modeling with large datasets and a rapid / robust framework for feature selection. Statistical modeling is used to design, test, and validate an accurate method for and identifying and classifying the features that predict individuals with cognitive frailty. The tree boosting model is used for the evaluation of multiple variables simultaneously and provides a high predictive value with low bias. The results presented within this dissertation create a foundation of understanding for a new aging condition and encourage translational research focused on the detection and prevention of cognitive frailty

A liquid biomarker signature of inflammatory proteins accurately predicts early pancreatic cancer progression during FOLFIRINOX chemotherapy

Background: Pancreatic ductal adenocarcinoma (PDAC) is often treated with FOLFIRINOX, a chemotherapy associated with high toxicity rates and variable efficacy. Therefore, it is crucial to identify patients at risk of early progression during treatment. This study aims to explore the potential of a multi-omics biomarker for predicting early PDAC progression by employing an in-depth mathematical modeling approach. Methods: Blood samples were collected from 58 PDAC patients undergoing FOLFIRINOX before and after the first cycle. These samples underwent gene (GEP) and inflammatory protein expression profiling (IPEP). We explored the predictive potential of exclusively IPEP through Stepwise (Backward) Multivariate Logistic Regression modeling. Additionally, we integrated GEP and IPEP using Bayesian Kernel Regression modeling, aiming to enhance predictive performance. Ultimately, the FOLFIRINOX IPEP (FFX-IPEP) signature was developed. Results: Our findings revealed that proteins exhibited superior predictive accuracy than genes. Consequently, the FFX-IPEP signature consisted of six proteins: AMN, BANK1, IL1RL2, ITGB6, MYO9B, and PRSS8. The signature effectively identified patients transitioning from disease control to progression early during FOLFIRINOX, achieving remarkable predictive accuracy with an AUC of 0.89 in an independent test set. Importantly, the FFX-IPEP signature outperformed the conventional CA19-9 tumor marker. Conclusions: Our six-protein FFX-IPEP signature holds solid potential as a liquid biomarker for the early prediction of PDAC progression during toxic FOLFIRINOX chemotherapy. Further validation in an external cohort is crucial to confirm the utility of the FFX-IPEP signature. Future studies should expand to predict progression under different chemotherapies to enhance the guidance of personalized treatment selection in PDAC.</p

A liquid biomarker signature of inflammatory proteins accurately predicts early pancreatic cancer progression during FOLFIRINOX chemotherapy

Background: Pancreatic ductal adenocarcinoma (PDAC) is often treated with FOLFIRINOX, a chemotherapy associated with high toxicity rates and variable efficacy. Therefore, it is crucial to identify patients at risk of early progression during treatment. This study aims to explore the potential of a multi-omics biomarker for predicting early PDAC progression by employing an in-depth mathematical modeling approach. Methods: Blood samples were collected from 58 PDAC patients undergoing FOLFIRINOX before and after the first cycle. These samples underwent gene (GEP) and inflammatory protein expression profiling (IPEP). We explored the predictive potential of exclusively IPEP through Stepwise (Backward) Multivariate Logistic Regression modeling. Additionally, we integrated GEP and IPEP using Bayesian Kernel Regression modeling, aiming to enhance predictive performance. Ultimately, the FOLFIRINOX IPEP (FFX-IPEP) signature was developed. Results: Our findings revealed that proteins exhibited superior predictive accuracy than genes. Consequently, the FFX-IPEP signature consisted of six proteins: AMN, BANK1, IL1RL2, ITGB6, MYO9B, and PRSS8. The signature effectively identified patients transitioning from disease control to progression early during FOLFIRINOX, achieving remarkable predictive accuracy with an AUC of 0.89 in an independent test set. Importantly, the FFX-IPEP signature outperformed the conventional CA19-9 tumor marker. Conclusions: Our six-protein FFX-IPEP signature holds solid potential as a liquid biomarker for the early prediction of PDAC progression during toxic FOLFIRINOX chemotherapy. Further validation in an external cohort is crucial to confirm the utility of the FFX-IPEP signature. Future studies should expand to predict progression under different chemotherapies to enhance the guidance of personalized treatment selection in PDAC.</p

Identifying Patients at High Risk of a Cardiovascular Event in the Near Future Current Status and Future Directions: Report of a National Heart, Lung, and Blood Institute Working Group

The National Heart, Lung, and Blood Institute convened a working group to provide basic and clinical research recommendations to the National Heart, Lung, and Blood Institute on the development of an integrated approach for identifying those individuals who are at high risk for a cardiovascular event such as acute coronary syndromes (ACS) or sudden cardiac death in the “near term.” The working group members defined near-term as occurring within 1 year of the time of assessment. The participants reviewed current clinical cardiology practices for risk assessment and state-of-the-science techniques in several areas, including biomarkers, proteomics, genetics, psychosocial factors, imaging, coagulation, and vascular and myocardial susceptibility. This report presents highlights of these reviews and a summary of suggested research directions

Infections and systemic inflammation are associated with lower plasma concentration of insulin-like growth factor I among Malawian children

Background: Insulin-like growth factor I (IGF-I) is the most important hormonal promoter of linear growth in infants and young children. Objectives: The objectives of this study were to compare plasma IGF-I concentration in a low- compared with a high-income country and characterize biological pathways leading to reduced IGF-I concentration in children in a low-income setting. Methods: We analyzed plasma IGF-I concentration from 716 Malawian and 80 Finnish children at 6-36 mo of age. In the Malawian children, we studied the association between IGF-I concentration and their environmental exposures; nutritional status; systemic and intestinal inflammation; malaria parasitemia and viral, bacterial, and parasitic enteric infections; as well as growth at 18 mo of age. We then conducted a pathway analysis to identify direct and indirect associations between these predictors and IGF-I concentration. Results: The mean IGF-I concentrations were similar in Malawi and Finland among 6-mo-old infants. At age 18 mo. the mean +/- SD concentration was almost double among the Finns compared with the Malawians [24.2 +/- 11.3 compared with 12.5 +/- 7.7 ng/mL., age- and sex-adjusted difference in mean (95% CI): 11.8 (9.9. 13.7) ng/mL; P <0.01]. Among 18-mo-old Malawians, plasma IGF-I concentration was inversely associated with systemic inflammation, malaria parasitemia, and intestinal Shigella. Campylobacter, and enterovirus infection and positively associated with the children's weight-for-length z score (WLZ), female sex, maternal height, mother's education, and dry season. Seasonally, mean plasma IGF-I concentration was highest in June and July and lowest in December and January, coinciding with changes in children's length gain and preceded by similar to 2 mo by the changes in their WLZ. Conclusions: The mean plasma IGF-I concentrations are similar in Malawi and Finland among 6-mo-old infants. Thereafter, mean concentrations rise markedly in Finland but not in Malawi. Systemic inflammation and clinically nonapparent infections are strongly associated with lower plasma IGF-I concentrations in Malawi through direct and indirect pathways.Peer reviewe

Precision medicine in distinct heart failure phenotypes: Focus on clinical epigenetics

Heart failure (HF) management is challenging due to high clinical heterogeneity of this disease which makes patients responding differently to evidence-based standard therapy established by the current reductionist approach. Better understanding of the genetic and epigenetic interactions may clarify molecular signatures underlying maladaptive responses in HF, including metabolic shift, myocardial injury, fibrosis, and mitochondrial dysfunction. DNA methylation, histone modifications and micro-RNA (miRNAs) may be major epigenetic players in the pathogenesis of HF. DNA hypermethylation of the kruppel-like factor 15 (KLF1.5) gene plays a key role in switching the failing heart from oxidative to glycolytic metabolism. Moreover, hypomethylation at H3K9 promoter level of atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) genes also leads to reactivation of fetal genes in man. The role of miRNAs has been investigated in HF patients undergoing heart transplantation, for whom miR-10a, miR-155, miR-31, and miR-92 may be putative useful prognostic biomarkers. Recently, higher RNA methylation levels have been observed in ischemic human hearts, opening the era of "epitranscriptome" in the pathogenesis of HF. Currently, hydralazine, statins, apabetalone, and omega-3 polyunsatured fatty acids (PUFA) are being tested in clinical trials to provide epigenetic-driven therapeutic interventions. Moreover, network-oriented analysis could advance current medical practice by focusing on protein-protein interactions (PPIs) perturbing the "cardiac" interactome. In this review, we provide an epigenetic map of maladaptive responses in HF patients. Furthermore, we propose the "EPi-transgeneratlonal network mOdeling for STratificatiOn of heaRt Morbidity" (EPIKO-STORM), a clinical research strategy offering novel opportunities to stratify the natural history of HF

Circulating Tumor DNA in Stage III Colorectal Cancer, beyond Minimal Residual Disease Detection, toward Assessment of Adjuvant Therapy Efficacy and Clinical Behavior of Recurrences

PURPOSE: Sensitive methods for risk stratification, monitoring therapeutic efficacy, and early relapse detection may have a major impact on treatment decisions and patient management for stage III colorectal cancer patients. Beyond assessing the predictive power of postoperative ctDNA detection, we explored the added benefits of serial analysis: assessing adjuvant chemotherapy (ACT) efficacy, early relapse detection, and ctDNA growth rates. EXPERIMENTAL DESIGN: We recruited 168 patients with stage III colorectal cancer treated with curative intent at Danish and Spanish hospitals between 2014 and 2019. To quantify ctDNA in plasma samples (n = 1,204), 16 patient-specific somatic single-nucleotide variants were profiled using multiplex-PCR, next-generation sequencing. RESULTS: Detection of ctDNA was a strong recurrence predictor postoperatively [HR = 7.0; 95% confidence interval (CI), 3.7–13.5; P < 0.001] and directly after ACT (HR = 50.76; 95% CI, 15.4–167; P < 0.001). The recurrence rate of postoperative ctDNA-positive patients treated with ACT was 80% (16/20). Only patients who cleared ctDNA permanently during ACT did not relapse. Serial ctDNA assessment after the end of treatment was similarly predictive of recurrence (HR = 50.80; 95% CI, 14.9–172; P < 0.001), and revealed two distinct rates of exponential ctDNA growth, slow (25% ctDNA-increase/month) and fast (143% ctDNA-increase/month; P < 0.001). The ctDNA growth rate was prognostic of survival (HR = 2.7; 95% CI, 1.1–6.7; P = 0.039). Serial ctDNA analysis every 3 months detected recurrence with a median lead-time of 9.8 months compared with standard-of-care computed tomography. CONCLUSIONS: Serial postoperative ctDNA analysis has a strong prognostic value and enables tumor growth rate assessment. The novel combination of ctDNA detection and growth rate assessment provides unique opportunities for guiding decision-making. See related commentary by Morris and George, p. 43

On stroke risk in type 2 diabetes : focus on glycemic control, insulin resistance, obesity and recovery

Background: People with type 2 diabetes (T2D) have an increased risk of cardiovascular disease. In this thesis the focus is on stroke with different aspects of aims, e.g. the risk of stroke in people with T2D, the role of glycemic control and insulin resistance (IR) in stroke, the potential intervention to minimize stroke damage, and the role of early-, and long-term outcome after carotid surgery in people with T2D. Method: We used data from different Swedish national quality registries in conjunction with Swedish national health registries. With the use of Cox regression analysis, utilizing inverse probability of treatment weighting, we focused on the outcome of stroke and death in relation to T2D, glycemic control (HbA1c), estimated glucose disposal rate (eGDR), i.e. a proxy for IR, and after carotid intervention. In addition, we used a mouse model to evaluate the effect of IR on stroke recovery. Results: There was a 50% relative increased risk of stroke and death in people with T2D compared to a matched general population. Glycemic control was independently associated with an increased risk of stroke and death (Study I). In people with T2D a low eGDR, i.e. high grade of IR, was associated with an increased stroke risk and death (Study II). Long-term dietary change led to weight loss with enhanced functional recovery after stroke. This effect was associated with pre-stroke normalization of fasting glucose and IR, and reduction of neuroinflammation together with enhancing neuroplasticity (Study III). After carotid surgery there was an increased early risk of stroke, but not for death, and in the long run there was an increased risk of stroke and death in people with T2D compared to people without diabetes (Study IV). Poor glycemic control (high HbA1c levels) in people with T2D have an increased long-term risk of stroke, and death after carotid surgery (Study V). Conclusions: The thesis expands the knowledge on stroke risk in T2D. Its relationship to glycemic control, and IR supporting the evidence for adequate management of glycemic control and the need for assessing IR. It also demonstrates that intervention with reversal of IR improve stroke recovery in rodents, a further research aim in people. There is an increased early-, and long-term risk after carotid intervention in people with T2D supporting further studies to reduce that risk