Phase III Randomized Study of SB5, an Adalimumab Biosimilar, Versus Reference Adalimumab in Patients With Moderate-to-Severe Rheumatoid Arthritis.

OBJECTIVE: SB5 is a biosimilar agent for adalimumab (ADA). The aim of this study was to evaluate the efficacy, pharmacokinetics (PK), safety, and immunogenicity of SB5 in comparison with reference ADA in patients with rheumatoid arthritis (RA). METHODS: In this phase III, randomized, double-blind, parallel-group study, patients with moderately to severely active RA despite treatment with methotrexate were randomized 1:1 to receive SB5 or reference ADA at a dosage of 40 mg subcutaneously every other week. The primary efficacy end point was the response rate based on the American College of Rheumatology 20% improvement criteria (ACR20) at week 24 in the per-protocol set (completer analysis). Additional end points included efficacy, PK, safety, and immunogenicity assessments. RESULTS: Of the 544 patients randomized to receive a study drug, the full analysis set comprised 542 patients (269 in the SB5 group, 273 in the reference ADA group) and the per-protocol set comprised 476 patients (239 receiving SB5, 237 receiving reference ADA). The ACR20 response rate at week 24 in the per-protocol set was equivalent between those receiving SB5 and those receiving reference ADA (72.4% and 72.2%, respectively); the difference in the ACR20 response rate (0.1%, [95% confidence interval -7.83%, 8.13%]) was within the predefined equivalence margin (±15%). Similar results were seen in the full analysis set (missing data being considered a nonresponse). The SB5 and reference ADA treatment groups were comparable across other end points, including the ACR 50% and ACR 70% improvement response rates, Disease Activity Score in 28 joints based on the erythrocyte sedimentation rate, PK data, incidence of treatment-emergent adverse events, and the antidrug antibody response. Subgroup analyses showed that the efficacy and safety of SB5 and reference ADA were comparable regardless of antidrug antibody status. CONCLUSION: The ACR20 response rate at week 24 was equivalent between patients treated with the biosimilar agent SB5 and those treated with reference ADA. SB5 and reference ADA were both well tolerated, with comparable safety profiles, in patients with RA.

52-week results of the phase 3 randomized study comparing SB4 with reference etanercept in patients with active rheumatoid arthritis.

Objective: To compare the 52-week efficacy and safety of SB4 [an etanercept biosimilar] with reference etanercept (ETN) in patients with active RA. Methods: In a phase 3, randomized, double-blind, multicentre study, patients with moderate to severe RA despite MTX treatment were randomized to receive 50 mg/week of s.c. SB4 or ETN up to week 52. Efficacy assessments included ACR response rates, 28-joint DAS, Simplified and Clinical Disease Activity Indices and changes in the modified total Sharp score (mTSS). Safety and immunogenicity were also evaluated. Results: A total of 596 patients were randomized to receive either SB4 (n = 299) or ETN (n = 297) and 505 (84.7%) patients completed 52 weeks of the study. At week 52, the ACR20 response rates in the per-protocol set were comparable between SB4 (80.8%) and ETN (81.5%). All efficacy results were comparable between the two groups and they were maintained up to week 52. Radiographic progression was also comparable and the change from baseline in the mTSS was 0.45 for SB4 and 0.74 for ETN. The safety profile of SB4 was similar to that of ETN and the incidence of anti-drug antibody development up to week 52 was 1.0 and 13.2% in the SB4 and ETN groups, respectively. Conclusion: Efficacy including radiographic progression was comparable between SB4 and ETN up to week 52. SB4 was well tolerated and had a similar safety profile to that of ETN. Trial registration number: ClinicalTrials.gov NCT01895309, EudraCT 2012-005026-30.

Long-term efficacy and safety in patients with rheumatoid arthritis continuing on SB4 or switching from reference etanercept to SB4.

OBJECTIVES: SB4 (Benepali, Brenzys) is a biosimilar of reference etanercept (ETN). In a randomised, double-blind, 52-week study, SB4 demonstrated comparable efficacy and safety to ETN in patients with rheumatoid arthritis (RA). The open-label extension period evaluated long-term efficacy, safety and immunogenicity when continuing SB4 versus switching from ETN to SB4. METHODS: In the randomised, double-blind phase, patients received weekly subcutaneous administration of 50 mg SB4 or ETN with background methotrexate for up to 52 weeks. Patients in the Czech Republic and Poland who completed the 52-week visit were enrolled in the open-label extension period and received SB4 for 48 additional weeks. Efficacy, safety and immunogenicity were assessed up to week 100. RESULTS: Of 245 patients entering the extension period, 126 continued to receive SB4 (SB4/SB4) and 119 switched to SB4 (ETN/SB4). American College of Rheumatology (ACR) response rates were sustained and comparable between SB4/SB4 and ETN/SB4 with ACR20 response rates at week 100 of 77.9% and 79.1%, respectively. Other efficacy results, including radiographic progression, were also comparable between the groups. After week 52, rates of treatment-emergent adverse events were 47.6% (SB4/SB4) and 48.7% (ETN/SB4); one patient/group developed non-neutralising antidrug antibodies. No cases of active tuberculosis or injection-site reactions were reported during the extension period. One patient (SB4/SB4) died of hepatic cancer. CONCLUSIONS: SB4 was effective and well tolerated over 2 years in patients with RA. Efficacy, safety and immunogenicity were comparable between the SB4/SB4 and ETN/SB4 groups, showing no risk associated with switching patients from ETN to SB4. TRIAL REGISTRATION NUMBER: NCT01895309; 2012-005026-30.

A phase III randomised, double-blind, parallel-group study comparing SB4 with etanercept reference product in patients with active rheumatoid arthritis despite methotrexate therapy.

OBJECTIVES: To compare the efficacy and safety of SB4 (an etanercept biosimilar) with reference product etanercept (ETN) in patients with moderate to severe rheumatoid arthritis (RA) despite methotrexate (MTX) therapy. METHODS: This is a phase III, randomised, double-blind, parallel-group, multicentre study with a 24-week primary endpoint. Patients with moderate to severe RA despite MTX treatment were randomised to receive weekly dose of 50 mg of subcutaneous SB4 or ETN. The primary endpoint was the American College of Rheumatology 20% (ACR20) response at week 24. Other efficacy endpoints as well as safety, immunogenicity and pharmacokinetic parameters were also measured. RESULTS: 596 patients were randomised to either SB4 (N=299) or ETN (N=297). The ACR20 response rate at week 24 in the per-protocol set was 78.1% for SB4 and 80.3% for ETN. The 95% CI of the adjusted treatment difference was -9.41% to 4.98%, which is completely contained within the predefined equivalence margin of -15% to 15%, indicating therapeutic equivalence between SB4 and ETN. Other efficacy endpoints and pharmacokinetic endpoints were comparable. The incidence of treatment-emergent adverse events was comparable (55.2% vs 58.2%), and the incidence of antidrug antibody development up to week 24 was lower in SB4 compared with ETN (0.7% vs 13.1%). CONCLUSIONS: SB4 was shown to be equivalent with ETN in terms of efficacy at week 24. SB4 was well tolerated with a lower immunogenicity profile. The safety profile of SB4 was comparable with that of ETN. TRIAL REGISTRATION NUMBERS: NCT01895309, EudraCT 2012-005026-30.

Collection and extraction of saliva DNA for next generation sequencing.

The preferred source of DNA in human genetics research is blood, or cell lines derived from blood, as these sources yield large quantities of high quality DNA. However, DNA extraction from saliva can yield high quality DNA with little to no degradation/fragmentation that is suitable for a variety of DNA assays without the expense of a phlebotomist and can even be acquired through the mail. However, at present, no saliva DNA collection/extraction protocols for next generation sequencing have been presented in the literature. This protocol optimizes parameters of saliva collection/storage and DNA extraction to be of sufficient quality and quantity for DNA assays with the highest standards, including microarray genotyping and next generation sequencing.

A genome scan for loci shared by autism spectrum disorder and language impairment.

OBJECTIVE: The authors conducted a genetic linkage study of families that have both autism spectrum disorder (ASD) and language-impaired probands to find common communication impairment loci. The hypothesis was that these families have a high genetic loading for impairments in language ability, thus influencing the language and communication deficits of the family members with ASD. Comprehensive behavioral phenotyping of the families also enabled linkage analysis of quantitative measures, including normal, subclinical, and disordered variation in all family members for the three general autism symptom domains: social, communication, and compulsive behaviors. METHOD: The primary linkage analysis coded persons with either ASD or specific language impairment as "affected." The secondary linkage analysis consisted of quantitative metrics of autism-associated behaviors capturing normal to clinically severe variation, measured in all family members. RESULTS: Linkage to language phenotypes was established at two novel chromosomal loci, 15q23-26 and 16p12. The secondary analysis of normal and disordered quantitative variation in social and compulsive behaviors established linkage to two loci for social behaviors (at 14q and 15q) and one locus for repetitive behaviors (at 13q). CONCLUSION: These data indicate shared etiology of ASD and specific language impairment at two novel loci. Additionally, nonlanguage phenotypes based on social aloofness and rigid personality traits showed compelling evidence for linkage in this study group. Further genetic mapping is warranted at these loci.

An eQTL biological data visualization challenge and approaches from the visualization community.

In 2011, the IEEE VisWeek conferences inaugurated a symposium on Biological Data Visualization. Like other domain-oriented Vis symposia, this symposium's purpose was to explore the unique characteristics and requirements of visualization within the domain, and to enhance both the Visualization and Bio/Life-Sciences communities by pushing Biological data sets and domain understanding into the Visualization community, and well-informed Visualization solutions back to the Biological community. Amongst several other activities, the BioVis symposium created a data analysis and visualization contest. Unlike many contests in other venues, where the purpose is primarily to allow entrants to demonstrate tour-de-force programming skills on sample problems with known solutions, the BioVis contest was intended to whet the participants' appetites for a tremendously challenging biological domain, and simultaneously produce viable tools for a biological grand challenge domain with no extant solutions. For this purpose expression Quantitative Trait Locus (eQTL) data analysis was selected. In the BioVis 2011 contest, we provided contestants with a synthetic eQTL data set containing real biological variation, as well as a spiked-in gene expression interaction network influenced by single nucleotide polymorphism (SNP) DNA variation and a hypothetical disease model. Contestants were asked to elucidate the pattern of SNPs and interactions that predicted an individual's disease state. 9 teams competed in the contest using a mixture of methods, some analytical and others through visual exploratory methods. Independent panels of visualization and biological experts judged entries. Awards were given for each panel's favorite entry, and an overall best entry agreed upon by both panels. Three special mention awards were given for particularly innovative and useful aspects of those entries. And further recognition was given to entries that correctly answered a bonus question about how a proposed "gene therapy" change to a SNP might change an individual's disease status, which served as a calibration for each approaches' applicability to a typical domain question. In the future, BioVis will continue the data analysis and visualization contest, maintaining the philosophy of providing new challenging questions in open-ended and dramatically underserved Bio/Life Sciences domains.

Variation in folate pathway genes contributes to risk of congenital heart defects among individuals with Down syndrome.

Cardiac abnormalities are one of the most common congenital defects observed in individuals with Down syndrome. Considerable research has implicated both folate deficiency and genetic variation in folate pathway genes with birth defects, including both congenital heart defects (CHD) and Down syndrome (DS). Here, we test variation in folate pathway genes for a role in the major DS-associated CHD atrioventricular septal defect (AVSD). In a group of 121 case families (mother, father, and proband with DS and AVSD) and 122 control families (mother, father, and proband with DS and no CHD), tag SNPs were genotyped in and around five folate pathway genes: 5,10-methylenetetrahyrdofolate reductase (MTHFR), methionine synthase (MTR), methionine synthase reductase (MTRR), cystathionine beta-synthase (CBS), and the reduced folate carrier (SLC19A1, RFC1). SLC19A1 was found to be associated with AVSD using a multilocus allele-sharing test. Individual SNP tests also showed nominally significant associations with odds ratios of between 1.34 and 3.78, depending on the SNP and genetic model. Interestingly, all marginally significant SNPs in SLC19A1 are in strong linkage disequilibrium (r(2)> or = 0.8) with the nonsynonymous coding SNP rs1051266 (c.80A>G), which has previously been associated with nonsyndromic cases of CHD. In addition to SLC19A1, the known functional polymorphism MTHFR c.1298A was over-transmitted to cases with AVSD (P=0.05) and under-transmitted to controls (P=0.02). We conclude, therefore, that disruption of the folate pathway contributes to the incidence of AVSD among individuals with DS.

Pooling-based genome-wide association study implicates gamma-glutamyltransferase 1 (GGT1) gene in pancreatic carcinogenesis.

BACKGROUND/AIMS: Knowledge regarding genetic factors that influence pancreatic cancer risk is currently limited. To identify novel pancreatic cancer susceptibility loci, we conducted a two-stage genome-wide association study. METHODS: The Affymetrix Genome-Wide Human SNP Array 6.0 and DNA pooling were used in the screening stage. Twenty-six single-nucleotide polymorphisms (SNPs) were selected for follow-up. These 26 lead SNPs and additionally selected tagSNPs for the regions around the lead SNPs were evaluated by individual genotyping of the pooling population and an independent validation population. RESULTS: Of the lead SNPs, the strongest association was found with rs4820599 located in the gamma-glutamyltransferase 1 (GGT1) gene. This SNP was significantly associated with pancreatic cancer risk in the validation population and the combined dataset (p(allele-based) = 0.019 and p(allele-based) = 0.003, respectively). Statistically significant associations were also observed with two GGT1 tagSNPs: rs2017869 and rs8135987. Lead SNP rs4820599 is in high linkage disequilibrium (LD; pairwise r(2): 0.69) and tagSNP rs2017869 is in strong LD (pairwise r(2): 0.96) with SNP rs5751901, which has been reported to be associated with increased GGT1 serum levels. GGT is expressed in the pancreas and plays a key role in glutathione metabolism. CONCLUSION: Our results suggest that common variation in the GGT1 gene may affect the risk of pancreatic cancer. .

Smarter clustering methods for SNP genotype calling.

MOTIVATION: Most genotyping technologies for single nucleotide polymorphism (SNP) markers use standard clustering methods to 'call' the SNP genotypes. These methods are not always optimal in distinguishing the genotype clusters of a SNP because they do not take advantage of specific features of the genotype calling problem. In particular, when family data are available, pedigree information is ignored. Furthermore, prior information about the distribution of the measurements for each cluster can be used to choose an appropriate model-based clustering method and can significantly improve the genotype calls. One special genotyping problem that has never been discussed in the literature is that of genotyping of trisomic individuals, such as individuals with Down syndrome. Calling trisomic genotypes is a more complicated problem, and the addition of external information becomes very important. RESULTS: In this article, we discuss the impact of incorporating external information into clustering algorithms to call the genotypes for both disomic and trisomic data. We also propose two new methods to call genotypes using family data. One is a modification of the K-means method and uses the pedigree information by updating all members of a family together. The other is a likelihood-based method that combines the Gaussian or beta-mixture model with pedigree information. We compare the performance of these two methods and some other existing methods using simulation studies. We also compare the performance of these methods on a real dataset generated by the Illumina platform (www.illumina.com). AVAILABILITY: The R code for the family-based genotype calling methods (SNPCaller) is available to be downloaded from the following website: http://watson.hgen.pitt.edu/register.

Linkage analysis of longitudinal data.

BACKGROUND: We propose a statistical model for linkage analysis of the longitudinal data. The proposed model is a mixed model based on the new Haseman and Elston model and allows several random effects. Specifically, the proposed model includes a random effect for correlation among sib pairs having one sibling in common, and one for the correlation among siblings from the same parents. RESULTS: The proposed model was applied to the analysis of the Genetic Analysis Workshop 13 simulated data set for a quantitative trait of the systolic blood pressure. A simple independence model and two kinds of random effects models yielded good power for detecting linkage for these data sets, while the random effects models performed slightly better than the independence model. Both random effects models showed similar performance. CONCLUSIONS: The proposed models seem not only quite useful in detecting linkage with the longitudinal data for the trait but also quite flexible. They can handle a wide class of correlation structures. Models with a more general class of covariance structure are desirable.