Genome-wide aggregated trans-effects on risk of type 1 diabetes: A test of the "omnigenic" sparse effector hypothesis of complex trait genetics.

The "omnigenic" hypothesis postulates that the polygenic effects of common SNPs on a typical complex trait are mediated through trans-effects on expression of a relatively sparse set of effector ("core") genes. We tested this hypothesis in a study of 4,964 cases of type 1 diabetes (T1D) and 7,497 controls by using summary statistics to calculate aggregated (excluding the HLA region) trans-scores for gene expression in blood. From associations of T1D with aggregated trans-scores, nine putative core genes were identified, of which three-STAT1, CTLA4 and FOXP3-are genes in which variants cause monogenic forms of autoimmune diabetes. Seven of these genes affect the activity of regulatory T cells, and two are involved in immune responses to microbial lipids. Four T1D-associated genomic regions could be identified as master regulators via trans-effects on gene expression. These results support the sparse effector hypothesis and reshape our understanding of the genetic architecture of T1D.

Visual extended reality tools in image-guided surgery in urology: a systematic review.

PURPOSE: The aim of this systematic review is to assess the clinical implications of employing various Extended Reality (XR) tools for image guidance in urological surgery. METHODS: In June 2023, a systematic electronic literature search was conducted using the Medline database (via PubMed), Embase (via Ovid), Scopus, and Web of Science. The search strategy was designed based on the PICO (Patients, Intervention, Comparison, Outcome) criteria. Study protocol was registered on PROSPERO (registry number CRD42023449025). We incorporated retrospective and prospective comparative studies, along with single-arm studies, which provided information on the use of XR, Mixed Reality (MR), Augmented Reality (AR), and Virtual Reality (VR) in urological surgical procedures. Studies that were not written in English, non-original investigations, and those involving experimental research on animals or cadavers were excluded from our analysis. The quality assessment of comparative and cohort studies was conducted utilizing the Newcastle-Ottawa scale, whilst for randomized controlled trials (RCTs), the Jadad scale was adopted. The level of evidence for each study was determined based on the guidelines provided by the Oxford Centre for Evidence-Based Medicine. RESULTS: The initial electronic search yielded 1,803 papers after removing duplicates. Among these, 58 publications underwent a comprehensive review, leading to the inclusion of 40 studies that met the specified criteria for analysis. 11, 20 and 9 studies tested XR on prostate cancer, kidney cancer and miscellaneous, including bladder cancer and lithiasis surgeries, respectively. Focusing on the different technologies 20, 15 and 5 explored the potential of VR, AR and MR. The majority of the included studies (i.e., 22) were prospective non-randomized, whilst 7 and 11 were RCT and retrospective studies respectively. The included studies that revealed how these new tools can be useful both in preoperative and intraoperative setting for a tailored surgical approach. CONCLUSIONS: AR, VR and MR techniques have emerged as highly effective new tools for image-guided surgery, especially for urologic oncology. Nevertheless, the complete clinical advantages of these innovations are still in the process of evaluation.

Development and validation of a cardiovascular risk prediction model in type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes. METHODS: A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552 person-years of follow-up were ascertained using hospital admissions and death registers. A Poisson regression model of CVD was developed and then validated in the Swedish National Diabetes Register (n = 33,183). We compared the percentage with a high 10 year CVD risk (i.e., ≥10%) using the model with the percentage eligible for statins using current guidelines by age. RESULTS: The age-standardised rate of CVD per 100,000 person-years was 4070 and 3429 in men and women, respectively, with type 1 diabetes in Scotland, and 4014 and 3956 in men and women in Sweden. The final model was well calibrated (Hosmer-Lemeshow test p > 0.05) and included a further 22 terms over a base model of age, sex and diabetes duration (C statistic 0.82; 95% CI 0.81, 0.83). The model increased the base model C statistic from 0.66 to 0.80, from 0.60 to 0.75 and from 0.62 to 0.68 in those aged <40, 40-59 and ≥ 60 years, respectively (all p values <0.005). The model required minimal calibration in Sweden and had a C statistic of 0.85. Under current guidelines, >90% of those aged 20-39 years and 100% of those ≥40 years with type 1 diabetes were eligible for statins, but it was not until age 65 upwards that 100% had a modelled risk of CVD ≥10% in 10 years. CONCLUSIONS/INTERPRETATION: A prediction tool such as that developed here can provide individualised risk predictions. This 10 year CVD risk prediction tool could facilitate patient discussions regarding appropriate statin prescribing. Apart from 10 year risk, such discussions may also consider longer-term CVD risk, the potential for greater benefits from early vs later statin intervention, the potential impact on quality of life of an early CVD event and evidence on safety, all of which could influence treatment decisions, particularly in younger people with type 1 diabetes.

Quantitative levels of serum N-glycans in type 1 diabetes and their association with kidney disease.

We investigated associations of quantitative levels of N-glycans with hemoglobin A1c (HbA1c), renal function and renal function decline in type 1 diabetes. We measured 46 total N-glycan peaks (GPs) on 1565 serum samples from the Scottish Diabetes Research Network Type 1 Bioresource Study (SDRNT1BIO) and a pool of healthy donors. Quantitation of absolute abundance of each GP used 2AB-labeled mannose-3 as a standard. We studied cross-sectional associations of GPs and derived measures with HbA1c, albumin/creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR), and prospective associations with incident albuminuria and final eGFR. All GPs were 1.4 to 3.2 times more abundant in SDRTN1BIO than in the healthy samples. Absolute levels of all GPs were slightly higher with higher HbA1c, with strongest associations for triantennary trigalactosylated disialylated, triantennary trigalactosylated trisialylated structures with core or outer arm fucose, and tetraantennary tetragalactosylated trisialylated glycans. Most GPs showed increased abundance with worsening ACR. Lower eGFR was associated with higher absolute GP levels, most significantly with biantennary digalactosylated disialylated glycans with and without bisect, triantennary trigalactosylated trisialylated glycans with and without outer arm fucose, and core fucosylated biantennary monogalactosylated monosialylated glycans. Although several GPs were inversely associated prospectively with final eGFR, cross-validated multivariable models did not improve prediction beyond clinical covariates. Elevated HbA1c is associated with an altered N-glycan profile in type 1 diabetes. Although we could not establish GPs to be prognostic of future renal function decline independently of HbA1c, further studies to evaluate their impact in the pathogenesis of diabetic kidney disease are warranted.

Predicting renal disease progression in a large contemporary cohort with type 1 diabetes mellitus.

AIMS/HYPOTHESIS: The aim of this study was to provide data from a contemporary population-representative cohort on rates and predictors of renal decline in type 1 diabetes. METHODS: We used data from a cohort of 5777 people with type 1 diabetes aged 16 and older, diagnosed before the age of 50, and representative of the adult population with type 1 diabetes in Scotland (Scottish Diabetes Research Network Type 1 Bioresource; SDRNT1BIO). We measured serum creatinine and urinary albumin/creatinine ratio (ACR) at recruitment and linked the data to the national electronic healthcare records. RESULTS: Median age was 44.1 years and diabetes duration 20.9 years. The prevalence of CKD stages G1, G2, G3 and G4 and end-stage renal disease (ESRD) was 64.0%, 29.3%, 5.4%, 0.6%, 0.7%, respectively. Micro/macroalbuminuria prevalence was 8.6% and 3.0%, respectively. The incidence rate of ESRD was 2.5 (95% CI 1.9, 3.2) per 1000 person-years. The majority (59%) of those with chronic kidney disease stages G3-G5 did not have albuminuria on the day of recruitment or previously. Over 11.6 years of observation, the median annual decline in eGFR was modest at -1.3 ml min-1 [1.73 m]-2 year-1 (interquartile range [IQR]: -2.2, -0.4). However, 14% experienced a more significant loss of at least 3 ml min-1 [1.73 m]-2. These decliners had more cardiovascular disease (OR 1.9, p = 5 × 10-5) and retinopathy (OR 1.3 p = 0.02). Adding HbA1c, prior cardiovascular disease, recent mean eGFR and prior trajectory of eGFR to a model with age, sex, diabetes duration, current eGFR and ACR maximised the prediction of final eGFR (r2 increment from 0.698 to 0.745, p < 10-16). Attempting to model nonlinearity in eGFR decline or to detect latent classes of decliners did not improve prediction. CONCLUSIONS: These data show much lower levels of kidney disease than historical estimates. However, early identification of those destined to experience significant decline in eGFR remains challenging.

Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes.

AIMS/HYPOTHESIS: We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR). METHODS: From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min-1 [1.73 m]-2, respectively (N = 1629), and with median 5.1 years of follow-up. Multiplexed ELISAs and single molecule array technology were used to measure nine serum biomarkers and 13 urine biomarkers based on our and others' prior work using large discovery and candidate studies. Associations with final eGFR and with progression to <30 ml min-1 [1.73] m-2, both adjusted for baseline eGFR, were tested using linear and logistic regression models. Parsimonious biomarker panels were identified using a penalised Bayesian approach, and their performance was evaluated through tenfold cross-validation and compared with using urinary ACR and other clinical record data. RESULTS: Seven serum and seven urine biomarkers were strongly associated with either final eGFR or progression to <30 ml min-1 [1.73 m]-2, adjusting for baseline eGFR and other covariates (all at p<2.3 × 10-3). Of these, associations of four serum biomarkers were independent of ACR for both outcomes. The strongest associations with both final eGFR and progression to <30 ml min-1 [1.73 m]-2 were for serum TNF receptor 1, kidney injury molecule 1, CD27 antigen, α-1-microglobulin and syndecan-1. These serum associations were also significant in normoalbuminuric participants for both outcomes. On top of baseline covariates, the r2 for prediction of final eGFR increased from 0.702 to 0.743 for serum biomarkers, and from 0.702 to 0.721 for ACR alone. The area under the receiver operating characteristic curve for progression to <30 ml min-1 [1.73 m]-2 increased from 0.876 to 0.953 for serum biomarkers, and to 0.911 for ACR alone. Other urinary biomarkers did not outperform ACR. CONCLUSIONS/INTERPRETATION: A parsimonious panel of serum biomarkers easily measurable along with serum creatinine may outperform ACR for predicting renal disease progression in type 1 diabetes, potentially obviating the need for urine testing.

Biomarkers associated with early stages of kidney disease in adolescents with type 1 diabetes.

OBJECTIVES: To identify biomarkers of renal disease in adolescents with type 1 diabetes (T1D) and to compare findings in adults with T1D. METHODS: Twenty-five serum biomarkers were measured, using a Luminex platform, in 553 adolescents (median [interquartile range] age: 13.9 [12.6, 15.2] years), recruited to the Adolescent Type 1 Diabetes Cardio-Renal Intervention Trial. Associations with baseline and final estimated glomerular filtration rate (eGFR), rapid decliner and rapid increaser phenotypes (eGFR slopes <-3 and > 3 mL/min/1.73m2 /year, respectively), and albumin-creatinine ratio (ACR) were assessed. Results were also compared with those obtained in 859 adults (age: 55.5 [46.1, 64.4) years) from the Scottish Diabetes Research Network Type 1 Bioresource. RESULTS: In the adolescent cohort, baseline eGFR was negatively associated with trefoil factor-3, cystatin C, and beta-2 microglobulin (B2M) (B coefficient[95%CI]: -0.19 [-0.27, -0.12], P = 7.0 × 10-7 ; -0.18 [-0.26, -0.11], P = 5.1 × 10-6 ; -0.12 [-0.20, -0.05], P = 1.6 × 10-3 ), in addition to clinical covariates. Final eGFR was negatively associated with osteopontin (-0.21 [-0.28, -0.14], P = 2.3 × 10-8 ) and cystatin C (-0.16 [-0.22, -0.09], P = 1.6 × 10-6 ). Rapid decliner phenotype was associated with osteopontin (OR: 1.83 [1.42, 2.41], P = 7.3 × 10-6 ), whereas rapid increaser phenotype was associated with fibroblast growth factor-23 (FGF-23) (1.59 [1.23, 2.04], P = 2.6 × 10-4 ). ACR was not associated with any of the biomarkers. In the adult cohort similar associations with eGFR were found; however, several additional biomarkers were associated with eGFR and ACR. CONCLUSIONS: In this young population with T1D and high rates of hyperfiltration, osteopontin was the most consistent biomarker associated with prospective changes in eGFR. FGF-23 was associated with eGFR increases, whereas trefoil factor-3, cystatin C, and B2M were associated with baseline eGFR.

Biomarker panels associated with progression of renal disease in type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to identify a sparse panel of biomarkers for improving the prediction of renal disease progression in type 1 diabetes. METHODS: We considered 859 individuals recruited from the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) and 315 individuals from the Finnish Diabetic Nephropathy (FinnDiane) study. All had an entry eGFR between 30 and 75 ml min-1[1.73 m]-2, with those from FinnDiane being oversampled for albuminuria. A total of 297 circulating biomarkers (30 proteins, 121 metabolites, 146 tryptic peptides) were measured in non-fasting serum samples using the Luminex platform and LC electrospray tandem MS (LC-MS/MS). We investigated associations with final eGFR adjusted for baseline eGFR and with rapid progression (a loss of more than 3 ml min-1[1.73 m]-2 year-1) using linear and logistic regression models. Panels of biomarkers were identified using a penalised Bayesian approach, and their performance was evaluated through 10-fold cross-validation and compared with using clinical record data alone. RESULTS: For final eGFR, 16 proteins and 30 metabolites or tryptic peptides showed significant association in SDRNT1BIO, and nine proteins and five metabolites or tryptic peptides in FinnDiane, beyond age, sex, diabetes duration, study day eGFR and length of follow-up (all at p < 10-4). The strongest associations were with CD27 antigen (CD27), kidney injury molecule 1 (KIM-1) and α1-microglobulin. Including the Luminex biomarkers on top of baseline covariates increased the r2 for prediction of final eGFR from 0.47 to 0.58 in SDRNT1BIO and from 0.33 to 0.48 in FinnDiane. At least 75% of the increment in r2 was attributable to CD27 and KIM-1. However, using the weighted average of historical eGFR gave similar performance to biomarkers. The LC-MS/MS platform performed less well. CONCLUSIONS/INTERPRETATION: Among a large set of associated biomarkers, a sparse panel of just CD27 and KIM-1 contains most of the predictive information for eGFR progression. The increment in prediction beyond clinical data was modest but potentially useful for oversampling individuals with rapid disease progression into clinical trials, especially where there is little information on prior eGFR trajectories.

Serum kidney injury molecule 1 and ß2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes.

AIMS/HYPOTHESIS: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. METHODS: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case-control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30-75 ml min-1 [1.73 m]-2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. RESULTS: Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and ß2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. CONCLUSIONS/INTERPRETATION: Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30-75 ml min-1 [1.73 m]-2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers.

Prediction of treatment response in rheumatoid arthritis patients using genome-wide SNP data.

Although a number of treatments are available for rheumatoid arthritis (RA), each of them shows a significant nonresponse rate in patients. Therefore, predicting a priori the likelihood of treatment response would be of great patient benefit. Here, we conducted a comparison of a variety of statistical methods for predicting three measures of treatment response, between baseline and 3 or 6 months, using genome-wide SNP data from RA patients available from the MAximising Therapeutic Utility in Rheumatoid Arthritis (MATURA) consortium. Two different treatments and 11 different statistical methods were evaluated. We used 10-fold cross validation to assess predictive performance, with nested 10-fold cross validation used to tune the model hyperparameters when required. Overall, we found that SNPs added very little prediction information to that obtained using clinical characteristics only, such as baseline trait value. This observation can be explained by the lack of strong genetic effects and the relatively small sample sizes available; in analysis of simulated and real data, with larger effects and/or larger sample sizes, prediction performance was much improved. Overall, methods that were consistent with the genetic architecture of the trait were able to achieve better predictive ability than methods that were not. For treatment response in RA, methods that assumed a complex underlying genetic architecture achieved slightly better prediction performance than methods that assumed a simplified genetic architecture.

Persistent C-peptide secretion in Type 1 diabetes and its relationship to the genetic architecture of diabetes.

BACKGROUND: The objective of this cross-sectional study was to explore the relationship of detectable C-peptide secretion in type 1 diabetes to clinical features and to the genetic architecture of diabetes. METHODS: C-peptide was measured in an untimed serum sample in the SDRNT1BIO cohort of 6076 Scottish people with clinically diagnosed type 1 diabetes or latent autoimmune diabetes of adulthood. Risk scores at loci previously associated with type 1 and type 2 diabetes were calculated from publicly available summary statistics. RESULTS: Prevalence of detectable C-peptide varied from 19% in those with onset before age 15 and duration greater than 15 years to 92% in those with onset after age 35 and duration less than 5 years. Twenty-nine percent of variance in C-peptide levels was accounted for by associations with male gender, late age at onset and short duration. The SNP heritability of residual C-peptide secretion adjusted for gender, age at onset and duration was estimated as 26%. Genotypic risk score for type 1 diabetes was inversely associated with detectable C-peptide secretion: the most strongly associated loci were the HLA and INS gene regions. A risk score for type 1 diabetes based on the HLA DR3 and DQ8-DR4 serotypes was strongly associated with early age at onset and inversely associated with C-peptide persistence. For C-peptide but not age at onset, there were strong associations with risk scores for type 1 and type 2 diabetes that were based on SNPs in the HLA region but not accounted for by HLA serotype. CONCLUSIONS: Persistence of C-peptide secretion varies widely in people clinically diagnosed as type 1 diabetes. C-peptide persistence is influenced by variants in the HLA region that are different from those determining risk of early-onset type 1 diabetes. Known risk loci for diabetes account for only a small proportion of the genetic effects on C-peptide persistence.

Association of response to TNF inhibitors in rheumatoid arthritis with quantitative trait loci for CD40 and CD39.

OBJECTIVES: We sought to investigate whether genetic effects on response to TNF inhibitors (TNFi) in rheumatoid arthritis (RA) could be localised by considering known genetic susceptibility loci for relevant traits and to evaluate the usefulness of these genetic loci for stratifying drug response. METHODS: We studied the relation of TNFi response, quantified by change in swollen joint counts ( Δ SJC) and erythrocyte sedimentation rate ( Δ ESR) with locus-specific scores constructed from genome-wide assocation study summary statistics in 2938 genotyped individuals: 37 scores for RA; scores for 19 immune cell traits; scores for expression or methylation of 93 genes with previously reported associations between transcript level and drug response. Multivariate associations were evaluated in penalised regression models by cross-validation. RESULTS: We detected a statistically significant association between Δ SJC and the RA score at the CD40 locus (p=0.0004) and an inverse association between Δ SJC and the score for expression of CD39 on CD4 T cells (p=0.00005). A previously reported association between CD39 expression on regulatory T cells and response to methotrexate was in the opposite direction. In stratified analysis by concomitant methotrexate treatment, the inverse association was stronger in the combination therapy group and dissipated in the TNFi monotherapy group. Overall, ability to predict TNFi response from genotypic scores was limited, with models explaining less than 1% of phenotypic variance. CONCLUSIONS: The association with the CD39 trait is difficult to interpret because patients with RA are often prescribed TNFi after failing to respond to methotrexate. The CD39 and CD40 pathways could be relevant for targeting drug therapy.

Validity of a two-component imaging-derived disease activity score for improved assessment of synovitis in early rheumatoid arthritis.

OBJECTIVES: Imaging of joint inflammation provides a standard against which to derive an updated DAS for RA. Our objectives were to develop and validate a DAS based on reweighting the DAS28 components to maximize association with US-assessed synovitis. METHODS: Early RA patients from two observational cohorts (n = 434 and n = 117) and a clinical trial (n = 59) were assessed at intervals up to 104 weeks from baseline; all US scans were within 1 week of clinical exam. There were 899, 163 and 183 visits in each cohort. Associations of combined US grey scale and power Doppler scores (GSPD) with 28 tender joint count and 28 swollen joint count (SJC28), CRP, ESR and general health visual analogue scale were examined in linear mixed model regressions. Cross-validation evaluated model predictive ability. Coefficients learned from training data defined a re-weighted DAS28 that was validated against radiographic progression in independent data (3037 observations; 717 patients). RESULTS: Of the conventional DAS28 components only SJC28 and CRP were associated with GSPD in all three development cohorts. A two-component model including SJC28 and CRP outperformed a four-component model (R2 = 0.235, 0.392, 0.380 vs 0.232, 0.380, 0.375, respectively). The re-weighted two-component DAS28CRP outperformed conventional DAS28 definitions in predicting GSPD (Δtest log-likelihood <-2.6, P < 0.01), Larsen score and presence of erosions. CONCLUSION: A score based on SJC28 and CRP alone demonstrated stronger associations with synovitis and radiographic progression than the original DAS28 and should be considered in research on pathophysiological manifestations of early RA. Implications for clinical management of RA remain to be established.

Genome-wide association study of response to tumour necrosis factor inhibitor therapy in rheumatoid arthritis.

Rheumatoid arthritis (RA) is characterised by chronic synovial joint inflammation. Treatment has been revolutionised by tumour necrosis factor alpha inhibitors (TNFi) but each available drug shows a significant non-response rate. We conducted a genome-wide association study of 1752 UK RA TNFi-treated patients to identify predictors of change in the Disease Activity Score 28 (DAS28) and subcomponents over 3-6 months. The rs7195994 variant at the FTO gene locus was associated with infliximab response when looking at a change in the swollen joint count (SJC28) subcomponent (p = 9.74 × 10-9). Capture Hi-C data show chromatin interactions in GM12878 cells between rs2540767, in high linkage disequilibrium with rs7195994 (R2 = 0.9) and IRX3, a neighbouring gene of FTO. IRX3 encodes a transcription factor involved in adipocyte remodelling and is regarded as the obesity gene at the FTO locus. Importantly, the rs7195994 association remained significantly associated following adjustment for BMI. In addition, using capture Hi-C data we showed interactions between TNFi-response associated variants and 16 RA susceptibility variants.

Genome-wide association study of response to methotrexate in early rheumatoid arthritis patients.

Methotrexate (MTX) monotherapy is a common first treatment for rheumatoid arthritis (RA), but many patients do not respond adequately. In order to identify genetic predictors of response, we have combined data from two consortia to carry out a genome-wide study of response to MTX in 1424 early RA patients of European ancestry. Clinical endpoints were change from baseline to 6 months after starting treatment in swollen 28-joint count, tender 28-joint count, C-reactive protein and the overall 3-component disease activity score (DAS28). No single nucleotide polymorphism (SNP) reached genome-wide statistical significance for any outcome measure. The strongest evidence for association was with rs168201 in NRG3 (p = 10-7 for change in DAS28). Some support was also seen for association with ZMIZ1, previously highlighted in a study of response to MTX in juvenile idiopathic arthritis. Follow-up in two smaller cohorts of 429 and 177 RA patients did not support these findings, although these cohorts were more heterogeneous.

Clinical applications and effectiveness of guided implant surgery: a critical review based on randomized controlled trials.

BACKGROUND: Nowadays implant placement protocols are widespread among clinicians all over the world. However, available literature, only partially analyses what can be potential benefits for the clinicians and patients, often focusing just on specific aspects, such as accuracy. The purpose of this review is to compare computer guided implant placement with conventional treatment protocols. METHODS: A search strategy according to the P-I-C-O format was developed and executed using an electronic MEDLINE plus manual search from 2000 up to December 2016. This review included only randomized controlled trials (RCTs) focusing on subjects treated with digital workflow for oral implant placement compared to conventional procedures. Data were extracted from eligible papers and analysed. All kinds of outcomes were considered, even patient-related and economical outcomes. RESULTS: The search strategy revealed 16 articles; additional manual searches selected further 21 publications. Afterwards the evaluation of articles, only two studies could be selected for subsequent data extraction. The two identified RCTs analysed primary outcomes as prosthesis failure, implant failure, biological or prosthetic complications, and secondary outcomes as periimplant marginal bone loss. One RCT evaluated also the duration of treatment, post-surgical progress, additional treatment costs and patient satisfaction. The other RCT focused instead on evaluating eventual improvement of patient's quality of life. In both selected studies, were not observed by the authors statistically significant differences between clinical cases treated with digital protocols and those treated with conventional ones. In one RCT, however post-surgical progress evaluation showed more patients' self-reported pain and swelling in conventional group. CONCLUSIONS: Within the limitation of this review, based on only two RCTs, the only evidence was that implant survival rate and effectiveness are similar for conventional and digital implant placement procedures. This is also confirmed by many other studies with however minor scientific evidence levels. Reduction of post-operative pain, surgical time and overall costs are discussed. Authors believe that scientific research should focus more in identifying which clinical situations can get greatest benefits from implant guided surgery. This should be done with research protocols such as RCT that assess comprehensively the advantages and disadvantages of fully digital surgical protocols.

Protein biomarkers for the prediction of cardiovascular disease in type 2 diabetes.

AIMS/HYPOTHESIS: We selected the most informative protein biomarkers for the prediction of incident cardiovascular disease (CVD) in people with type 2 diabetes. METHODS: In this nested case-control study we measured 42 candidate CVD biomarkers in 1,123 incident CVD cases and 1,187 controls with type 2 diabetes selected from five European centres. Combinations of biomarkers were selected using cross-validated logistic regression models. Model prediction was assessed using the area under the receiver operating characteristic curve (AUROC). RESULTS: Sixteen biomarkers showed univariate associations with incident CVD. The most predictive subset selected by forward selection methods contained six biomarkers: N-terminal pro-B-type natriuretic peptide (OR 1.69 per 1 SD, 95% CI 1.47, 1.95), high-sensitivity troponin T (OR 1.29, 95% CI 1.11, 1.51), IL-6 (OR 1.13, 95% CI 1.02, 1.25), IL-15 (OR 1.15, 95% CI 1.01, 1.31), apolipoprotein C-III (OR 0.79, 95% CI 0.70, 0.88) and soluble receptor for AGE (OR 0.84, 95% CI 0.76, 0.94). The prediction of CVD beyond clinical covariates improved from an AUROC of 0.66 to 0.72 (AUROC for Framingham Risk Score covariates 0.59). In addition to the biomarkers, the most important clinical covariates for improving prediction beyond the Framingham covariates were estimated GFR, insulin therapy and HbA1c. CONCLUSIONS/INTERPRETATION: We identified six protein biomarkers that in combination with clinical covariates improved the prediction of our model beyond the Framingham Score covariates. Biomarkers can contribute to improved prediction of CVD in diabetes but clinical data including measures of renal function and diabetes-specific factors not included in the Framingham Risk Score are also needed.

Biomarkers of rapid chronic kidney disease progression in type 2 diabetes.

Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and evaluate for predictive performance. Ultimately, 30 biomarkers showed significant associations with rapid progression and adjusted for clinical characteristics. A panel of 14 biomarkers increased the area under the ROC curve from 0.706 (clinical data alone) to 0.868. Biomarkers selected included fibroblast growth factor-21, the symmetric to asymmetric dimethylarginine ratio, ß2-microglobulin, C16-acylcarnitine, and kidney injury molecule-1. Use of more extensive clinical data including prebaseline eGFR slope improved prediction but to a lesser extent than biomarkers (area under the ROC curve of 0.793). Thus we identified several novel associations of biomarkers with CKD progression and the utility of a small panel of biomarkers to improve prediction.

Extending admixture mapping to nuclear pedigrees: application to sarcoidosis.

We describe statistical methods that extend the application of admixture mapping from unrelated individuals to nuclear pedigrees, allowing existing pedigree-based collections to be fully exploited. Computational challenges have been overcome by developing a fast algorithm that exploits the factorial structure of the underlying model of ancestry transitions. This has been implemented as an extension of the program ADMIXMAP. We demonstrate the application of the method to a study of sarcoidosis in African Americans that has previously been analyzed only as an admixture mapping study restricted to unrelated individuals. Although the ancestry signals detected in this pedigree analysis are generally similar to those detected in the earlier analysis of unrelated cases, we are able to extract more information and this yields a much sharper exclusion map; using the classical criterion of an LOD score of minus 2, the pedigree analysis is able to exclude a risk ratio of 2 or more associated with African ancestry over 96% of the genome, compared with only 83% in the earlier analysis of unrelated individuals only. Although the pedigree extension of ADMIXMAP can use ancestry-informative markers only at relatively low density, it can use imputed ancestry states from programs such as WINPOP or HAPMIX that use dense SNP marker genotypes for admixture mapping. This extends both the efficiency and the range of application of this powerful gene mapping method.

Shear bond strength of one-step self-etch adhesives to enamel: effect of acid pretreatment.

AIM: The purposes of this study were to evaluate the effect of surface pretreatment with phosphoric acid on the enamel bond strength of four-one-step self-etch adhesives with different pH values. MATERIAL AND METHODS: One hundred bovine permanent mandibular incisors were used. The materials used in this study included four-one-step self-etch adhesives with different pH values: Adper(™) Easy Bond Self-Etch Adhesive (ph = 0,8-1), Futurabond NR (ph = 1,4), G-aenial Bond (ph = 1,5), Clearfil(3) S Bond (ph = 2,7). One two-step self-etch adhesive (Clearfil SE Bond/ph = 0,8-1) was used as control. The teeth were assigned into two subgroups according to bonding procedure. In the first subgroup (n = 50), no pretreatment agent was applied. In the second subgroup (n = 50), etching was performed using 37% phosphoric acid for 30 s. After adhesive systems application, a nanohybrid composite resin was inserted into the enamel surface. The specimens were placed in a universal testing machine (Model 3343, Instron Corp., Canton, Mass., USA). After the testing procedure, the fractured surfaces were examined with an optical microscope at a magnification of 10× to determine failure modes. The adhesive remnant index (ARI) was used to assess the amount of adhesive left on the enamel surface. RESULTS: Descriptive statistics of the shear bond strength and frequency distribution of ARI scores were calculated. CONCLUSIONS: Enamel pretreatment with phosphoric acid significantly increased bond strength values of all the adhesives tested. No significant differences in bond strength were detected among the four different one-step self-etch adhesives with different pH. Two-step self-etch adhesive showed the highest bond strength.