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68 result(s) for "Rajan Philip, M."
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Molecular Beam Epitaxial Growth and Device Characterization of AlGaN Nanowire Ultraviolet-B Light-Emitting Diodes
We report on the design and fabrication of high performance AlxGa1−xN nanowire ultraviolet (UV) light-emitting diodes (LEDs) on silicon substrate by molecular beam epitaxy. The emission wavelength and surface morphology of nanowires can be controlled by varying the growth parameters that include substrate temperatures and/or Aluminum/Gallium flux ratios. The devices exhibit excellent current-voltage characteristics with relatively low resistance. Such nanowire LEDs generate strong emission in the UV-B band tuning from 290 nm to 330 nm. The electroluminescence spectra show virtually invariant blue-shift under injection current from 50 mA to 400 mA, suggesting the presence of a negligible quantum-confined Stark effect. Moreover, we have shown that, the AlGaN nanowire LEDs using periodic structures, can achieve high light extraction efficiency of ~ 89% and 92% for emissions at 290nm and 320nm, respectively. The randomly arranged nanowire 290 nm UV LEDs exhibit light extraction efficiency of ~ 56% which is higher compared to current AlGaN based thin-film UV LEDs.
Large scale meta-analysis characterizes genetic architecture for common psoriasis associated variants
Psoriasis is a complex disease of skin with a prevalence of about 2%. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for psoriasis to date, including data from eight different Caucasian cohorts, with a combined effective sample size >39,000 individuals. We identified 16 additional psoriasis susceptibility loci achieving genome-wide significance, increasing the number of identified loci to 63 for European-origin individuals. Functional analysis highlighted the roles of interferon signalling and the NFκB cascade, and we showed that the psoriasis signals are enriched in regulatory elements from different T cells (CD8 + T-cells and CD4 + T-cells including T H 0, T H 1 and T H 17). The identified loci explain ∼28% of the genetic heritability and generate a discriminatory genetic risk score (AUC=0.76 in our sample) that is significantly correlated with age at onset ( p= 2 × 10 −89 ). This study provides a comprehensive layout for the genetic architecture of common variants for psoriasis. Psoriasis is an immune-mediated skin disease with a complex genetic architecture. Here, Elder and colleagues identify 16 novel psoriasis susceptibility loci using GWAS meta-analysis with a combined effective sample size of over 39,000 individuals.
Analysis of long non-coding RNAs highlights tissue-specific expression patterns and epigenetic profiles in normal and psoriatic skin
Although analysis pipelines have been developed to use RNA-seq to identify long non-coding RNAs (lncRNAs), inference of their biological and pathological relevance remains a challenge. As a result, most transcriptome studies of autoimmune disease have only assessed protein-coding transcripts. We used RNA-seq data from 99 lesional psoriatic, 27 uninvolved psoriatic, and 90 normal skin biopsies, and applied computational approaches to identify and characterize expressed lncRNAs. We detect 2,942 previously annotated and 1,080 novel lncRNAs which are expected to be skin specific. Notably, over 40% of the novel lncRNAs are differentially expressed and the proportions of differentially expressed transcripts among protein-coding mRNAs and previously-annotated lncRNAs are lower in psoriasis lesions versus uninvolved or normal skin. We find that many lncRNAs, in particular those that are differentially expressed, are co-expressed with genes involved in immune related functions, and that novel lncRNAs are enriched for localization in the epidermal differentiation complex. We also identify distinct tissue-specific expression patterns and epigenetic profiles for novel lncRNAs, some of which are shown to be regulated by cytokine treatment in cultured human keratinocytes. Together, our results implicate many lncRNAs in the immunopathogenesis of psoriasis, and our results provide a resource for lncRNA studies in other autoimmune diseases.
Genetic signature to provide robust risk assessment of psoriatic arthritis development in psoriasis patients
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. Approximately 30% of psoriasis patients develop psoriatic arthritis (PsA) and early diagnosis is crucial for the management of PsA. Here, Patrick et al. develop a computational pipeline involving statistical and machine-learning methods that can assess the risk of progression to PsA based on genetic markers.
Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data
Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount. The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team. Around 80 000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation. Implementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene–phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial. Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health.
Enhanced meta-analysis and replication studies identify five new psoriasis susceptibility loci
Psoriasis is a chronic autoimmune disease with complex genetic architecture. Previous genome-wide association studies (GWAS) and a recent meta-analysis using Immunochip data have uncovered 36 susceptibility loci. Here, we extend our previous meta-analysis of European ancestry by refined genotype calling and imputation and by the addition of 5,033 cases and 5,707 controls. The combined analysis, consisting of over 15,000 cases and 27,000 controls, identifies five new psoriasis susceptibility loci at genome-wide significance ( P <5 × 10 −8 ). The newly identified signals include two that reside in intergenic regions (1q31.1 and 5p13.1) and three residing near PLCL2 (3p24.3), NFKBIZ (3q12.3) and CAMK2G (10q22.2). We further demonstrate that NFKBIZ is a TRAF3IP2 -dependent target of IL-17 signalling in human skin keratinocytes, thereby functionally linking two strong candidate genes. These results further integrate the genetics and immunology of psoriasis, suggesting new avenues for functional analysis and improved therapies. About 2% of the population are affected by psoriasis, a chronic skin disease with complex genetics. Here Tsoi et al. conduct a meta-analysis of several genome-wide association studies and identify five novel loci, helping to further our understanding of the biology behind this condition.
Transcriptome Analysis of Psoriasis in a Large Case–Control Sample: RNA-Seq Provides Insights into Disease Mechanisms
To increase our understanding of psoriasis, we used high-throughput complementary DNA sequencing (RNA-seq) to assay the transcriptomes of lesional psoriatic and normal skin. We sequenced polyadenylated RNA-derived complementary DNAs from 92 psoriatic and 82 normal punch biopsies, generating an average of ∼38 million single-end 80-bp reads per sample. Comparison of 42 samples examined by both RNA-seq and microarray revealed marked differences in sensitivity, with transcripts identified only by RNA-seq having much lower expression than those also identified by microarray. RNA-seq identified many more differentially expressed transcripts enriched in immune system processes. Weighted gene coexpression network analysis (WGCNA) revealed multiple modules of coordinately expressed epidermal differentiation genes, overlapping significantly with genes regulated by the long noncoding RNA TINCR, its target gene, staufen-1 (STAU1), the p63 target gene ZNF750, and its target KLF4. Other coordinately expressed modules were enriched for lymphoid and/or myeloid signature transcripts and genes induced by IL-17 in keratinocytes. Dermally expressed genes were significantly downregulated in psoriatic biopsies, most likely because of expansion of the epidermal compartment. These results show the power of WGCNA to elucidate gene regulatory circuits in psoriasis, and emphasize the influence of tissue architecture in both differential expression and coexpression analysis.
Genome-wide association analysis identifies three psoriasis susceptibility loci
James Elder and colleagues report meta-analyses of two psoriasis genome-wide association studies with replication in additional cohorts. They make use of imputation using both the HapMap and initial 1000 Genomes Project datasets and identify three new psoriasis susceptibility loci. We carried out a meta-analysis of two recent psoriasis genome-wide association studies 1 , 2 with a combined discovery sample of 1,831 affected individuals (cases) and 2,546 controls. One hundred and two loci selected based on P value rankings were followed up in a three-stage replication study including 4,064 cases and 4,685 controls from Michigan, Toronto, Newfoundland and Germany. In the combined meta-analysis, we identified three new susceptibility loci, including one at NOS2 (rs4795067, combined P = 4 × 10 −11 ), one at FBXL19 (rs10782001, combined P = 9 × 10 −10 ) and one near PSMA6 - NFKBIA (rs12586317, combined P = 2 × 10 −8 ). All three loci were also associated with psoriatic arthritis (rs4795067, combined P = 1 × 10 −5 ; rs10782001, combined P = 4 × 10 −8 ; and rs12586317, combined P = 6 × 10 −5 ) and purely cutaneous psoriasis (rs4795067, combined P = 1 × 10 −8 ; rs10782001, combined P = 2 × 10 −6 ; and rs12586317, combined P = 1 × 10 −6 ). We also replicated a recently identified 3 association signal near RNF114 (rs495337, combined P = 2 × 10 −7 ).
In utero adenine base editing corrects multi-organ pathology in a lethal lysosomal storage disease
In utero base editing has the potential to correct disease-causing mutations before the onset of pathology. Mucopolysaccharidosis type I (MPS-IH, Hurler syndrome) is a lysosomal storage disease (LSD) affecting multiple organs, often leading to early postnatal cardiopulmonary demise. We assessed in utero adeno-associated virus serotype 9 (AAV9) delivery of an adenine base editor (ABE) targeting the Idua G→A (W392X) mutation in the MPS-IH mouse, corresponding to the common IDUA G→A (W402X) mutation in MPS-IH patients. Here we show efficient long-term W392X correction in hepatocytes and cardiomyocytes and low-level editing in the brain. In utero editing was associated with improved survival and amelioration of metabolic, musculoskeletal, and cardiac disease. This proof-of-concept study demonstrates the possibility of efficiently performing therapeutic base editing in multiple organs before birth via a clinically relevant delivery mechanism, highlighting the potential of this approach for MPS-IH and other genetic diseases. Lysosomal storage diseases like mucopolysaccharidosis type I (MPS I) cause pathology before birth and result in early morbidity and mortality. Here, the authors show that in utero base editing mediates multi-organ phenotypic and survival benefits in a mouse model recapitulating a common human MPSI mutation.