Serum Proteomic Signatures in Cervical Cancer: Current Status and Future Directions.

In 2020, the World Health Organization (WHO) reported 604,000 new diagnoses of cervical cancer (CC) worldwide, and over 300,000 CC-related fatalities. The vast majority of CC cases are caused by persistent human papillomavirus (HPV) infections. HPV-related CC incidence and mortality rates have declined worldwide because of increased HPV vaccination and CC screening with the Papanicolaou test (PAP test). Despite these significant improvements, developing countries face difficulty implementing these programs, while developed nations are challenged with identifying HPV-independent cases. Molecular and proteomic information obtained from blood or tumor samples have a strong potential to provide information on malignancy progression and response to therapy in CC. There is a large amount of published biomarker data related to CC available but the extensive validation required by the FDA approval for clinical use is lacking. The ability of researchers to use the big data obtained from clinical studies and to draw meaningful relationships from these data are two obstacles that must be overcome for implementation into clinical practice. We report on identified multimarker panels of serum proteomic studies in CC for the past 5 years, the potential for modern computational biology efforts, and the utilization of nationwide biobanks to bridge the gap between multivariate protein signature development and the prediction of clinically relevant CC patient outcomes.

A candidate panel of eight urinary proteins shows potential of early diagnosis and risk assessment for diabetic kidney disease in type 1 diabetes.

Diabetic kidney disease (DKD) poses a significant health challenge for individuals with diabetes. At its initial stages, DKD often presents asymptomatically, and the standard for non-invasive diagnosis, the albumin-creatinine ratio (ACR), employs discrete categorizations (normal, microalbuminuria, macroalbuminuria) with limitations in sensitivity and specificity across diverse population cohorts. Single biomarker reliance further restricts the predictive value in clinical settings. Given the escalating prevalence of diabetes, our study uses proteomic technologies to identify novel urinary proteins as supplementary DKD biomarkers. A total of 158 T1D subjects provided urine samples, with 28 (15 DKD; 13 non-DKD) used in the discovery stage and 131 (45 DKD; 40 pDKD; 46 non-DKD) used in the confirmation. We identified eight proteins (A1BG, AMBP, AZGP1, BTD, RBP4, ORM2, GM2A, and PGCP), all of which demonstrated excellent area-under-the-curve (AUC) values (0.959 to 0.995) in distinguishing DKD from non-DKD. Furthermore, this multi-marker panel successfully segregated the most ambiguous group (microalbuminuria) into three distinct clusters, with 80% of subjects aligning either as DKD or non-DKD. The remaining 20% exhibited continued uncertainty. Overall, the use of these candidate urinary proteins allowed for the better classification of DKD and offered potential for significant improvements in the early identification of DKD in T1D populations.

Multiplex analysis of inflammatory proteins associated with risk of coronary artery disease in type-1 diabetes patients.

BACKGROUND: Chronic uncontrolled hyperglycemia, a precursor to chronic low-grade inflammation, is a leading cause of coronary artery disease (CAD) due to plaque buildup in type-1 diabetes (T1D) patients. We evaluated levels of 22 inflammatory markers in cross-sectional serum samples from 1222 subjects to evaluate their potential as risk factors for CAD in T1D patients. HYPOTHESIS: Circulating levels of markers of inflammation may be the risk factors for incident CAD. METHODS: The T1D subjects were divided into two groups: those without CAD (n = 1107) and with CAD (n = 115). Serum levels of proteins were assayed using multiplex immunoassays on a Luminex Platform. Differences between the two groups were made by univariate analysis. Multivariate logistic regression was used to ascertain the potential of proteins as risk factors for CAD. Influence of age, duration of diabetes, sex, hypertension, and dyslipidemia was determined in a stepwise manner. Serum levels of 22 proteins were combined into a composite score using Ridge regression for risk-based stratification. RESULTS: Mean levels of CRP, IGFBP1, IGFBP2, insulin-like growth factors binding protein-6 (IGFBP6), MMP1, SAA, sTNFRI, and sTNFRII were elevated in CAD patients (n = 115) compared to T1D patients without CAD (nCAD, n = 1107). After adjusting for age, duration of diabetes, sex, hypertension, and dyslipidemia, higher levels of sTNFRI (odds ratio [OR] = 2.18, 1.1 × 10-3 ), sTNFRII (OR = 1.52, 1 × 10-2 ), and IGFBP6 (OR = 3.62, 1.8 × 10-3 ) were significantly associated with CAD. The composite score based on Ridge regression, was able to stratify CAD patients into low, medium, and high-risk groups. CONCLUSIONS: The results show activation of the TNF pathway in CAD patients. Evaluating these markers in serum can be a potential tool for identifying high-risk T1D patients for intensive anti-inflammatory therapeutic interventions.

Ovarian recurrence risk assessment using machine learning, clinical information, and serum protein levels to predict survival in high grade ovarian cancer.

In ovarian cancer, there is no current method to accurately predict recurrence after a complete response to chemotherapy. Here, we develop a machine learning risk score using serum proteomics for the prediction of early recurrence of ovarian cancer after initial treatment. The developed risk score was validated in an independent cohort with serum collected prospectively during the remission period. In the discovery cohort, patients scored as low-risk had a median time to recurrence (TTR) that was not reached at 10 years compared to 10.5 months (HR 4.66, p < 0.001) in high-risk patients. In the validation cohort, low-risk patients had a median TTR which was not reached compared to 4.7 months in high-risk patients (HR 4.67, p = 0.009). In advanced-stage patients with a CA125 < 10, low-risk patients had a median TTR of 68 months compared to 6 months in high-risk patients (HR 2.91, p = 0.02). The developed risk score was capable of distinguishing the duration of remission in ovarian cancer patients. This score may help guide maintenance therapy and develop innovative treatments in patients at risk at high-risk of recurrence.

High serum levels of inflammatory markers are associated with early recurrence in patients with high-grade serous ovarian cancer after platinum therapy.

OBJECTIVE: To determine if inflammatory biomarkers can predict the long-term outcome of platinum therapy in patients with high-grade serous ovarian cancer. METHODS: Women diagnosed with high-grade serous epithelial ovarian cancer (n = 70) at a single institution were enrolled in a prospective serum collection study between 2005 and 2020. Seventeen markers of inflammation and oxidative stress were measured in serum samples on a chemistry analyzer. Association was tested for serum levels with progression-free survival (PFS), time to recurrence (TTR), overall survival (OS), and time to death (TTD) using Cox proportional hazards and Kaplan-Meier curves. Patient survival was censored at 10 years. RESULTS: Higher serum levels of LDH were associated with worse PFS (HR 2.57, p = 0.028). High serum levels of BAP (HR 0.38, p = 0.025), GSP (HR 0.40, p = 0.040), HDL-c (HR 0.27, p = 0.002), and MG (HR 0.36, p = 0.017) were associated with improved PFS. Higher expression of LDH was associated with worse OS (HR 2.16, p = 0.023). Higher levels of CK.nac (HR 0.39, p = 0.033) and HDL-c (HR 0.35, p = 0.029) were associated with improved OS. Similar outcomes were found with TTR and TTD analyses. CONCLUSION: General inflammatory biomarkers may serve as a guide for prognosis and treatment benefit. Future studies needed to further define their role in predicting prognosis or how these markers may affect response to therapy.

Efficacy and Safety of Stempeucel in Osteoarthritis of the Knee: A Phase 3 Randomized, Double-Blind, Multicenter, Placebo-Controlled Study.

BACKGROUND: Osteoarthritis is a chronic, progressive, and degenerative condition with limited therapy options. Recently, biologic therapies have been an evolving option for the management of osteoarthritis. PURPOSE: To assess whether allogenic mesenchymal stromal cells (MSCs) have the potential to improve functional parameters and induce cartilage regeneration in patients with osteoarthritis. STUDY DESIGN: Randomized controlled trial; Level of evidence, 1. METHODS: A total of 146 patients with grade 2 and 3 osteoarthritis were randomized to either an MSC group or placebo group with a ratio of 1:1. There were 73 patients per group who received either a single intra-articular injection of bone marrow-derived MSCs (BMMSCs; 25 million cells) or placebo, followed by 20 mg per 2 mL of hyaluronic acid under ultrasound guidance. The primary endpoint was the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score. The secondary endpoints were WOMAC subscores for pain, stiffness, and physical function; the visual analog scale score for pain; and magnetic resonance imaging findings using T2 mapping and cartilage volume. RESULTS: Overall, 65 patients from the BMMSC group and 68 patients from the placebo group completed 12-month follow-up. The BMMSC group showed significant improvements in the WOMAC total score compared with the placebo group at 6 and 12 months (percentage change: -23.64% [95% CI, -32.88 to -14.40] at 6 months and -45.60% [95% CI, -55.97 to -35.23] at 12 months P < .001; percentage change, -44.3%). BMMSCs significantly improved WOMAC pain, stiffness, and physical function subscores as well as visual analog scale scores at 6 and 12 months (P < .001). T2 mapping showed that there was no worsening of deep cartilage in the medial femorotibial compartment of the knee in the BMMSC group at 12-month follow-up, whereas in the placebo group, there was significant and gradual worsening of cartilage (P < .001). Cartilage volume did not change significantly in the BMMSC group. There were 5 adverse events that were possibly/probably related to the study drug and consisted of injection-site swelling and pain, which improved within a few days. CONCLUSION: In this small randomized trial, BMMSCs proved to be safe and effective for the treatment of grade 2 and 3 osteoarthritis. The intervention was simple and easy to administer, provided sustained relief of pain and stiffness, improved physical function, and prevented worsening of cartilage quality for ≥12 months. REGISTRATION: CTRI/2018/09/015785 (National Institutes of Health and Clinical Trials Registry-India).

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma.

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Use of a glycomics array to establish the anti-carbohydrate antibody repertoire in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease, characterized by the presence of autoantibodies to protein and non-protein antigens. Here we report the identification of specific anti-carbohydrate antibodies (ACAs) that are associated with pathogenesis and progression to T1D. We compare circulatory levels of ACAs against 202 glycans in a cross-sectional cohort of T1D patients (n = 278) and healthy controls (n = 298), as well as in a longitudinal cohort (n = 112). We identify 11 clusters of ACAs associated with glycan function class. Clusters enriched for aminoglycosides, blood group A and B antigens, glycolipids, ganglio-series, and O-linked glycans are associated with progression to T1D. ACAs against gentamicin and its related structures, G418 and sisomicin, are also associated with islet autoimmunity. ACAs improve discrimination of T1D status of individuals over a model with only clinical variables and are potential biomarkers for T1D.

Development of a Single Molecule Counting Assay to Differentiate Chromophobe Renal Cancer and Oncocytoma in Clinics.

Malignant chromophobe renal cancer (chRCC) and benign oncocytoma (RO) are two renal tumor types difficult to differentiate using histology and immunohistochemistry-based methods because of their similarity in appearance. We previously developed a transcriptomics-based classification pipeline with "Chromophobe-Oncocytoma Gene Signature" (COGS) on a single-molecule counting platform. Renal cancer patients (n = 32, chRCC = 17, RO = 15) were recruited from Augusta University Medical Center (AUMC). Formalin-fixed paraffin-embedded (FFPE) blocks from their excised tumors were collected. We created a custom single-molecule counting code set for COGS to assay RNA from FFPE blocks. Utilizing hematoxylin-eosin stain, pathologists were able to correctly classify these tumor types (91.8%). Our unsupervised learning with UMAP (Uniform manifold approximation and projection, accuracy = 0.97) and hierarchical clustering (accuracy = 1.0) identified two clusters congruent with their histology. We next developed and compared four supervised models (random forest, support vector machine, generalized linear model with L2 regularization, and supervised UMAP). Supervised UMAP has shown to classify all the cases correctly (sensitivity = 1, specificity = 1, accuracy = 1) followed by random forest models (sensitivity = 0.84, specificity = 1, accuracy = 1). This pipeline can be used as a clinical tool by pathologists to differentiate chRCC from RO.

Oncocytoma-Related Gene Signature to Differentiate Chromophobe Renal Cancer and Oncocytoma Using Machine Learning.

Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised learning in the discovery dataset (97.8% accuracy) with density based UMAP (DBU). The top 30 genes were identified by univariate gene expression analysis and ROC analysis, to create a gene signature called COGS. COGS, combined with DBU, was able to differentiate chRCC from RO in the discovery dataset with an accuracy of 97.8%. The classification accuracy of COGS was validated in an independent meta-dataset consisting of TCGA-KICH and GSE12090, where COGS could differentiate chRCC from RO with 100% accuracy. The differentially expressed genes were involved in carbohydrate metabolism, transcriptomic regulation by TP53, beta-catenin-dependent Wnt signaling, and cytokine (IL-4 and IL-13) signaling highly active in cancer cells. Using multiple datasets and machine learning, we constructed and validated COGS as a tool that can differentiate chRCC from RO and complement histology in routine clinical practice to distinguish these two tumors.

Multiplex Glycan Bead Array (MGBA ) for High Throughput and High Content Analyses of Glycan-Binding Proteins Including Natural Anti-Glycan Antibodies.

We present here detailed protocols for the newly developed multiplex glycan bead array (MGBA) for the high throughput and high content analyses of various glycan-binding proteins including anti-glycan antibodies. This platform takes advantage of the commercially available Luminex beads to construct glycan arrays that are easily customizable at will and anytime by researchers. The platform allows the simultaneous analyses of up to 500 glycans and 384 samples at a time. By using multiple arrays, a researcher can analyze thousands of glycans and tens of thousands of samples within a short period. The assay is highly sensitive, specific, reproducible, economic, and fast. Furthermore, the bead array platform is approved for use in clinical settings, speeding up the translation of laboratory discoveries into patient care.

Emerging urinary alpha-synuclein and miRNA biomarkers in Parkinson's disease.

Parkinson's disease (PD) is one of the most common neurodegenerative diseases after Alzheimer's disease (AD), afflicting adults above the age of sixty irrespective of gender, race, ethnicity, and social status. PD is characterized by motor dysfunctions, displaying resting tremor, rigidity, bradykinesia, and postural imbalance. Non-motor symptoms, including rapid eye movement (REM) behavior disorder, constipation, and loss of sense of smell, typically occur many years before the appearance of the PD motor symptoms that lead to a diagnosis. The loss of dopaminergic neurons in the substantia nigra, which leads to the motor symptoms seen in PD, is associated with the deposition of aggregated, misfolded α-Synuclein (α-Syn, SNCA) proteins forming Lewy Bodies. Additionally, dysregulation of miRNA (a short form of mRNA) may contribute to the developing pathophysiology in PD and other diseases such as cancer. Overexpression of α-Syn and miRNA in human samples has been found in PD, AD, and dementia. Therefore, evaluating these molecules in urine, present either in the free form or in association with extracellular vesicles of biological fluids, may lead to early biomarkers for clinical diagnosis. Collection of urine is non-invasive and thus beneficial, particularly in geriatric populations, for biomarker analysis. Considering the expression and function of α-Syn and miRNA, we predict that they can be used as early biomarkers in the diagnosis and prognosis of neurodegenerative diseases.

Low-Dose Niacin Supplementation Improves Motor Function in US Veterans with Parkinson's Disease: A Single-Center, Randomized, Placebo-Controlled Trial.

A six-month double-blind, placebo-controlled randomized study was conducted to ascertain whether low-dose daily niacin supplementation would improve motor symptoms in Parkinson's disease (PD) patients. A total of 47 PD patients were assigned to receive low-dose niacin or a placebo. At the end of the double-blind phase, all participants received open-label niacin for the next six months. All patients were evaluated at baseline, after six months, and after one year of treatment. The primary outcome measure was the Unified Parkinson's Disease Rating Scale III (UPDRS III) scores. Secondary outcome measures were depression, sleep quality, mental flexibility and cognition, and physical fatigue. Niacin treatment was well-tolerated by forty-five subjects. The mean [95% CI] change in UPDRS III scores at six months of placebo was -0.05 [95% CI, -2.4 to 2.32], and niacin was -1.06 [95% CI, -3.68 to 1.57]. From six to twelve months when both groups received open-label niacin supplementation, the average UPDRS III scores significantly decreased for the placebo group by 4.58 [95% CI, -0.85 to 8.30] and the niacin group by 4.63 [95% CI, 1.42 to 7.83] points. Low-dose niacin supplementation is a well-tolerated adjunct therapy and may improve motor function in PD when taken over a longer period.

T1DMicro: A Clinical Risk Calculator for Type 1 Diabetes Related Microvascular Complications.

Development of complications in type 1 diabetes patients can be reduced by modifying risk factors. We used a cross-sectional cohort of 1646 patients diagnosed with type 1 diabetes (T1D) to develop a clinical risk score for diabetic peripheral neuropathy (DPN), autonomic neuropathy (AN), retinopathy (DR), and nephropathy (DN). Of these patients, 199 (12.1%) had DPN, 63 (3.8%) had AN, 244 (14.9%) had DR, and 88 (5.4%) had DN. We selected five variables to include in each of the four microvascular complications risk models: age, age of T1D diagnosis, duration of T1D, and average systolic blood pressure and HbA1C over the last three clinic visits. These variables were selected for their strong evidence of association with diabetic complications in the literature and because they are modifiable risk factors. We found the optimism-corrected R2 and Harrell's C statistic were 0.39 and 0.87 for DPN, 0.24 and 0.86 for AN, 0.49 and 0.91 for DR, and 0.22 and 0.83 for DN, respectively. This tool was built to help inform patients of their current risk of microvascular complications and to motivate patients to control their HbA1c and systolic blood pressure in order to reduce their risk of these complications.

Chronic Kidney Disease: Role of Diet for a Reduction in the Severity of the Disease.

Chronic kidney disease affects ~37 million adults in the US, and it is often undiagnosed due to a lack of apparent symptoms in early stages. Chronic kidney disease (CKD) interferes with the body's physiological and biological mechanisms, such as fluid electrolyte and pH balance, blood pressure regulation, excretion of toxins and waste, vitamin D metabolism, and hormonal regulation. Many CKD patients are at risk of hyperkalemia, hyperphosphatemia, chronic metabolic acidosis, bone deterioration, blood pressure abnormalities, and edema. These risks may be minimized, and the disease's progression may be slowed through careful monitoring of protein, phosphorus, potassium, sodium, and calcium, relieving symptoms experienced by CKD patients. In this review, the current Kidney Disease Outcomes Quality Initiative (KDOQI) recommendations are highlighted, reflecting the 2020 update, including explanations for the pathophysiology behind the recommendations. The Dietary Approaches to Stop Hypertension, the Mediterranean diet, and the whole foods plant-based diet are currently being examined for their potential role in delaying CKD progression. Biological explanations for why the whole foods plant-based diet may benefit CKD patients compared to diets that include animal products are examined. Strong evidence continues to support the importance of diet meeting the daily requirement in the prevention and progression of kidney disease, and medical nutrition therapy with a registered dietitian is a critical aspect in medical intervention for CKD.

Niacin Enhancement for Parkinson's Disease: An Effectiveness Trial.

We previously reported that individuals with Parkinson's disease (PD) present with lower vitamin B3 levels compared to controls. It may be related to carbidopa interaction, defective tryptophan metabolism, and stresses of night sleep disorder. Vitamin B3 is the energy source for all cells by producing NAD+ and NADP+ in redox reactions of oxidative phosphorylation. Thus, some symptoms of PD such as fatigue, sleep dysfunction, and mood changes may be related to the deficiency of vitamin B3. Here, we conducted an effectiveness trial to determine the effect of 12 months of low-dose niacin (a vitamin B3 derivative) enhancement in PD individuals. An average of 9 ± 6-point improvement in the Unified Parkinson's Disease Rating Scale (UPDRS) III (motor) score was observed after 12 months of daily niacin compared to the expected decline in score (effect size = 0.78, 95% CI = 7-11). Additionally, secondary outcome measures improved. Notably, handwriting size increased, fatigue perception decreased, mood improved, frontal beta rhythm during quiet stance increased, and stance postural sway amplitude and range of acceleration decreased. Set shifting, however, as measured by the Trail Making-B test, worsened from 66 to 96 s. Other measures did not change after 12 months, but it is not clear whether this represents a positive benefit of the vitamin. For example, while the quality of night sleep remained the same, there was a trend towards a decrease in the frequency of awakening episodes. These results suggest that niacin enhancement has the potential to maintain or improve quality of life in PD and slow disease progression.

Serum Levels of Inflammatory Proteins Are Associated With Peripheral Neuropathy in a Cross-Sectional Type-1 Diabetes Cohort.

Chronic low-grade inflammation is involved in the pathogenesis of type-1 diabetes (T1D) and its complications. In this cross-section study design, we investigated association between serum levels of soluble cytokine receptors with presence of peripheral neuropathy in 694 type-1 diabetes patients. Sex, age, blood pressure, smoking, alcohol intake, HbA1c and lipid profile, presence of DPN (peripheral and autonomic), retinopathy and nephropathy was obtained from patient's chart. Measurement of soluble cytokine receptors, markers of systemic and vascular inflammation was done using multiplex immunoassays. Serum levels were elevated in in DPN patients, independent of gender, age and duration of diabetes. Crude odds ratios were significantly associated with presence of DPN for 15/22 proteins. The Odds ratio (OR) remained unchanged for sTNFRI (1.72, p=0.00001), sTNFRII (1.45, p=0.0027), sIL2Rα (1.40, p=0.0023), IGFBP6 (1.51, p=0.0032) and CRP (1.47, p=0.0046) after adjusting for confounding variables, HbA1C, hypertension and dyslipidemia. Further we showed risk of DPN is associated with increase in serum levels of sTNFRI (OR=11.2, p<10), sIL2Rα (8.69, p<10-15), sNTFRII (4.8, p<10-8) and MMP2 (4.5, p<10-5). We combined the serum concentration using ridge regression, into a composite score, which can stratify the DPN patients into low, medium and high-risk groups. Our results here show activation of inflammatory pathway in DPN patients, and could be a potential clinical tool to identify T1D patients for therapeutic intervention of anti-inflammatory therapies.

Retrospective Validation of a 168-Gene Expression Signature for Glioma Classification on a Single Molecule Counting Platform.

Gene expression profiling has been shown to be comparable to other molecular methods for glioma classification. We sought to validate a gene-expression based glioma classification method. Formalin-fixed paraffin embedded tissue and flash frozen tissue collected at the Augusta University (AU) Pathology Department between 2000-2019 were identified and 2 mm cores were taken. The RNA was extracted from these cores after deparaffinization and bead homogenization. One hundred sixty-eight genes were evaluated in the RNA samples on the nCounter instrument. Forty-eight gliomas were classified using a supervised learning algorithm trained by using data from The Cancer Genome Atlas. An ensemble of 1000 linear support vector models classified 30 glioma samples into TP1 with classification confidence of 0.99. Glioma patients in TP1 group have a poorer survival (HR (95% CI) = 4.5 (1.3-15.4), p = 0.005) with median survival time of 12.1 months, compared to non-TP1 groups. Network analysis revealed that cell cycle genes play an important role in distinguishing TP1 from non-TP1 cases and that these genes may play an important role in glioma survival. This could be a good clinical pipeline for molecular classification of gliomas.

The 3p21.31 genetic locus promotes progression to type 1 diabetes through the CCR2/CCL2 pathway.

Multiple cross-sectional and longitudinal studies have shown that serum levels of the chemokine ligand 2 (CCL-2) are associated with type 1 diabetes (T1D), although the direction of effect differs. We assessed CCL-2 serum levels in a longitudinal cohort to clarify this association, combined with genetic data to elucidate the regulatory role of CCL-2 in T1D pathogenesis. The Diabetes Autoimmunity Study in the Young (DAISY) followed 310 subjects with high risk of developing T1D. Of these, 42 became persistently seropositive for islet autoantibodies but did not develop T1D (non-progressors); 48 did develop T1D (progressors). CCL-2 serum levels among the three study groups were compared using linear mixed models adjusting for age, sex, HLA genotype, and family history of T1D. Summary statistics were obtained from the CCL-2 protein quantitative trait loci (pQTL) and CCR2 expression QTL (eQTL) studies. The T1D fine mapping association data were provided by the Type 1 Diabetes Genetics Consortium (T1DGC). Serum CCL-2 levels were significantly lower in both progressors (p = 0.004) and non-progressors (p = 0.005), compared to controls. Two SNPs (rs1799988 and rs746492) in the 3p21.31 genetic locus, which includes the CCL-2 receptor, CCR2, were associated with increased CCR2 expression (p = 8.2e-5 and 5.2e-5, respectively), decreased CCL-2 serum level (p = 2.41e-9 and 6.21e-9, respectively), and increased risk of T1D (p = 7.9e-5 and 7.9e-5, respectively). The 3p21.31 genetic region is associated with developing T1D through regulatory control of the CCR2/CCL2 immune pathway.

Niacin and Butyrate: Nutraceuticals Targeting Dysbiosis and Intestinal Permeability in Parkinson's Disease.

Dysbiosis is implicated by many studies in the pathogenesis of Parkinson's disease (PD). Advances in sequencing technology and computing have resulted in confounding data regarding pathogenic bacterial profiles in conditions such as PD. Changes in the microbiome with reductions in short-chain fatty acid (SCFA)-producing bacteria and increases in endotoxin-producing bacteria likely contribute to the pathogenesis of PD. GPR109A, a G-protein coupled receptor found on the surface of the intestinal epithelium and immune cells, plays a key role in controlling intestinal permeability and the inflammatory cascade. The absence of GPR109A receptors is associated with decreased concentration of tight junction proteins, leading to increased intestinal permeability and susceptibility to inflammation. In inflammatory states, butyrate acts via GPR109A to increase concentrations of tight junction proteins and improve intestinal permeability. Niacin deficiency is exacerbated in PD by dopaminergic medications. Niacin supplementation has been shown to shift macrophage polarization from pro-inflammatory to an anti-inflammatory profile. Niacin and butyrate, promising nutrients and unique ligands for the G protein-coupled receptor GPR109A, are reviewed in this paper in detail.