While genomic data sharing can facilitate important health research and discovery benefits, these must be balanced against potential privacy risks and harms to individuals. Understanding public ...attitudes and perspectives on data sharing is important given these potential risks and to inform genomic research and policy that aligns with public preferences and needs. A cross sectional online survey measured attitudes towards genomic data sharing among members of the general public in an Eastern Canadian province. With evolving regulations and guidelines for genomics research and data sharing, it is important to consider the perspectives of participants most impacted by these changes. Participant information materials and informed consent documents must be explicit about the safeguards in place to protect genomic data and the policies governing the sharing of data. Increased public awareness of the role of research ethics boards and of the need for genomic data sharing more broadly is also needed.
Psoriasis and psoriatic arthritis (PsA) are heterogeneous diseases. While both have a strong genetic basis, it is strongest for PsA, where fewer investigators are studying its genetics. Over the last ...year the number of independent genetic loci associated with psoriasis has substantially increased, mostly due to completion of multiple genome-wide association studies (GWAS) in psoriasis. At least 2 GWAS efforts are now under way in PsA to identify novel genes in this disease; a metaanalysis of genome-wide scans and further studies must follow to examine the genetics of disease expression, epistatic interaction, and gene-environment interaction. In the long term, it is anticipated that genome-wide sequencing is likely to generate another wave of novel genes in PsA. At the annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) in Stockholm, Sweden, in 2009, members discussed issues and challenges regarding the advancement of the genetics of PsA; results of those discussions are summarized here.
Biological therapies have dramatically improved the therapeutic landscape of psoriatic arthritis (PsA); however, 40-50% of patients are primary non-responders with response rates declining ...significantly with each successive biological therapy. Therefore, there is a pressing need to develop a coherent strategy for effective initial and subsequent selection of biologic agents. We interrogated 40 PsA patients initiating either tumour necrosis factor inhibitors (TNFi) or interleukin-17A inhibitors (17Ai) for active PsA. Patients achieving low disease activity according to the Disease Activity Index for PsA (DAPSA) at 3 months were classified as responders. Baseline and 3-month CD4
transcript profiling were performed, and novel signaling pathways were identified using a multi-omics profiling and integrative computational analysis approach. Using transcriptomic data at initiation of therapy, we identified over 100 differentially expressed genes (DEGs) that differentiated IL-17Ai response from non-response and TNFi response from non-response. Integration of cell-type-specific DEGs with protein-protein interactions and further comprehensive pathway enrichment analysis revealed several pathways. Rho GTPase signaling pathway exhibited a strong signal specific to IL-17Ai response and the genes, RAC1 and ROCKs, are supported by results from prior research. Our detailed network and pathway analyses have identified the rewiring of Rho GTPase pathways as potential markers of response to IL17Ai but not TNFi. These results need further verification.
Psoriatic arthritis (PsA) is a complex chronic musculoskeletal condition that occurs in ~30% of psoriasis patients. Currently, no systematic strategy is available that utilizes the differences in ...genetic architecture between PsA and cutaneous-only psoriasis (PsC) to assess PsA risk before symptoms appear. Here, we introduce a computational pipeline for predicting PsA among psoriasis patients using data from six cohorts with >7000 genotyped PsA and PsC patients. We identify 9 new loci for psoriasis or its subtypes and achieve 0.82 area under the receiver operator curve in distinguishing PsA vs. PsC when using 200 genetic markers. Among the top 5% of our PsA prediction we achieve >90% precision with 100% specificity and 16% recall for predicting PsA among psoriatic patients, using conditional inference forest or shrinkage discriminant analysis. Combining statistical and machine-learning techniques, we show that the underlying genetic differences between psoriasis subtypes can be used for individualized subtype risk assessment.
The long-term safety was assessed in patients with psoriatic arthritis who were treated with ixekizumab in three clinical trials (SPIRIT-P1/-P2/-P3).
Integrated safety data from three trials ...(controlled and uncontrolled), including two pivotal phase 3, randomized, double-blind clinical trials: SPIRIT-P1 and SPIRIT-P2, were assessed. Safety data were integrated from the all ixekizumab exposure safety population (defined as all patients receiving ≥ 1 dose of ixekizumab). We report exposure-adjusted incidence rates (IRs) per 100 patient-years (PY) at 1-year intervals up to 3 years for adverse events.
Total exposure to IXE reached 1822.2 PY (1118 patients). The IRs/100 PY for the following treatment discontinuations were as follows: adverse events (5.3); serious infections (1.3); injection-site reactions (12.7); infections (34.2); and deaths (0.3). The IRs for treatment-emergent adverse events decreased or remained stable over time, the most common being upper respiratory tract infection, nasopharyngitis, and injection-site reactions. The IRs for serious adverse events and serious infections remained stable over time, whereas for injection-site reactions and general infections, IRs decreased with longer ixekizumab exposure. Opportunistic infections were limited to oral and esophageal candida and localized herpes zoster. No suicide or self-injury-related behaviors were reported. The IRs/100 PY for safety topics of special interest included inflammatory bowel disease (adjudicated; 0.1), depression (1.6), malignancies (0.7), and major adverse cardiovascular events (0.6).
The findings of this integrated safety analysis in patients with psoriatic arthritis are consistent with the known safety profile of ixekizumab. No unexpected safety signals were observed with ixekizumab treatment in patients with psoriatic arthritis.
SPIRIT-P1 (NCT01695239; Registered August 08, 2012), SPIRIT-P2 (NCT02349295; September 23, 2014), and SPIRIT-P3 (NCT02584855; August 04, 2015).
Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a ...heterozygote's two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (ncases = 5,337), type 1 diabetes (T1D; ncases = 5,567), psoriasis vulgaris (ncases = 3,089), idiopathic achalasia (ncases = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 × 10(-12); T1D, P = 2.4 × 10(-10); psoriasis, P = 5.9 × 10(-6); celiac disease, P = 1.2 × 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 × 10(-3); T1D, P = 8.6 × 10(-27); celiac disease, P = 6.0 × 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model.
Osteoarthritis (OA) is the most prevalent form of arthritis and the major cause of disability and overall diminution of quality of life in the elderly population. Currently there is no cure for OA, ...partly due to the large gaps in our understanding of its underlying molecular and cellular mechanisms. Macrophage migration inhibitory factor (MIF) is a procytokine that mediates pleiotropic inflammatory effects in inflammatory diseases such as rheumatoid arthritis (RA) and ankylosing spondylitis (AS). However, data on the role of MIF in OA is limited with conflicting results. We undertook this study to investigate the role of MIF in OA by examining MIF genotype, mRNA expression, and protein levels in the Newfoundland Osteoarthritis Study.
One hundred nineteen end-stage knee/hip OA patients, 16 RA patients, and 113 healthy controls were included in the study. Two polymorphisms in the MIF gene, rs755622, and -794 CATT
, were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and PCR followed by automated capillary electrophoresis, respectively. MIF mRNA levels in articular cartilage and subchondral bone were measured by quantitative polymerase chain reaction. Plasma concentrations of MIF, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1 beta (IL-1β) were measured by enzyme-linked immunosorbent assay.
rs755622 and -794 CATT
genotypes were not associated with MIF mRNA or protein levels or OA (all p ≥ 0.19). MIF mRNA level in cartilage was lower in OA patients than in controls (p = 0.028) and RA patients (p = 0.004), while the levels in bone were comparable between OA patients and controls (p = 0.165). MIF protein level in plasma was lower in OA patients than in controls (p = 3.01 × 10
), while the levels of TNF-α, IL-6 and IL-1β in plasma were all significantly higher in OA patients than in controls (all p ≤ 0.0007). Multivariable logistic regression showed lower MIF and higher IL-1β protein levels in plasma were independently associated with OA (OR per SD increase = 0.10 and 8.08; 95% CI = 0.04-0.19 and 4.42-16.82, respectively), but TNF-α and IL-6 became non-significant.
Reduced MIF mRNA and protein expression in OA patients suggested MIF might have a protective role in OA and could serve as a biomarker to differentiate OA from other joint disorders.
Psoriasis vulgaris (PsV) risk is strongly associated with variation within the major histocompatibility complex (MHC) region, but its genetic architecture has yet to be fully elucidated. Here, we ...conducted a large-scale fine-mapping study of PsV risk in the MHC region in 9,247 PsV-affected individuals and 13,589 controls of European descent by imputing class I and II human leukocyte antigen (HLA) genes from SNP genotype data. In addition, we imputed sequence variants for MICA, an MHC HLA-like gene that has been associated with PsV, to evaluate association at that locus as well. We observed that HLA-C∗06:02 demonstrated the lowest p value for overall PsV risk (p = 1.7 × 10−364). Stepwise analysis revealed multiple HLA-C∗06:02-independent risk variants in both class I and class II HLA genes for PsV susceptibility (HLA-C∗12:03, HLA-B amino acid positions 67 and 9, HLA-A amino acid position 95, and HLA-DQα1 amino acid position 53; p < 5.0 × 10−8), but no apparent risk conferred by MICA. We further evaluated risk of two major clinical subtypes of PsV, psoriatic arthritis (PsA; n = 3,038) and cutaneous psoriasis (PsC; n = 3,098). We found that risk heterogeneity between PsA and PsC might be driven by HLA-B amino acid position 45 (pomnibus = 2.2 × 10−11), indicating that different genetic factors underlie the overall risk of PsV and the risk of specific PsV subphenotypes. Our study illustrates the value of high-resolution HLA and MICA imputation for fine mapping causal variants in the MHC.
Psoriasis is a common inflammatory disorder of the skin and other organs. We have determined that mutations in CARD14, encoding a nuclear factor of kappa light chain enhancer in B cells (NF-kB) ...activator within skin epidermis, account for PSORS2. Here, we describe fifteen additional rare missense variants in CARD14, their distribution in seven psoriasis cohorts (>6,000 cases and >4,000 controls), and their effects on NF-kB activation and the transcriptome of keratinocytes. There were more CARD14 rare variants in cases than in controls (burden test p value = 0.0015). Some variants were only seen in a single case, and these included putative pathogenic mutations (c.424G>A p.Glu142Lys and c.425A>G p.Glu142Gly) and the generalized-pustular-psoriasis mutation, c.413A>C (p.Glu138Ala); these three mutations lie within the coiled-coil domain of CARD14. The c.349G>A (p.Gly117Ser) familial-psoriasis mutation was present at a frequency of 0.0005 in cases of European ancestry. CARD14 variants led to a range of NF-kB activities; in particular, putative pathogenic variants led to levels >2.5× higher than did wild-type CARD14. Two variants (c.511C>A p.His171Asn and c.536G>A p.Arg179His) required stimulation with tumor necrosis factor alpha (TNF-α) to achieve significant increases in NF-kB levels. Transcriptome profiling of wild-type and variant CARD14 transfectants in keratinocytes differentiated probably pathogenic mutations from neutral variants such as polymorphisms. Over 20 CARD14 polymorphisms were also genotyped, and meta-analysis revealed an association between psoriasis and rs11652075 (c.2458C>T p.Arg820Trp; p value = 2.1 × 10−6). In the two largest psoriasis cohorts, evidence for association increased when rs11652075 was conditioned on HLA-Cw∗0602 (PSORS1). These studies contribute to our understanding of the genetic basis of psoriasis and illustrate the challenges faced in identifying pathogenic variants in common disease.
There is a strong familial component to psoriatic disease as well as a complex array of genetic, immunologic, and environmental factors. The dominant genetic effect is located on chromosome 6p21.3 ...within the major histocompatibility complex region, accounting for one-third of genetic contribution. Genome-wide association studies (GWAS) identified additional genes, including skin barrier function, innate immune response, and adaptive immune response genes. To better understand disease susceptibility and progression requires replication in larger cohorts, fine-mapping efforts, new technologies, and functional studies of genetic variants, gene-gene interactions and gene-environmental interactions. New technologies available include next-generation sequencing, copy number variation analysis, and epigenetics.
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