Faculty Bibliography
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64
Specimen Collection for Translational Studies in Hidradenitis Suppurativa
Hidradenitis suppurativa (HS) is a chronic inflammatory disorder characterized by painful nodules, sinus tracts, and scars occurring predominantly in intertriginous regions. The prevalence of HS is currently 0.053-4%, with a predominance in African-American women and has been linked to low socioeconomic status. The majority of the reported literature is retrospective, population based, epidemiologic studies. In this regard, there is a need to establish a repository of biospecimens, which represent appropriate gender and racial demographics amongst HS patients. These efforts will diminish knowledge gaps in understanding the disease pathophysiology. Hence, we sought to outline a step-by-step protocol detailing how we established our HS biobank to facilitate the formation of other HS tissue banks. Equipping researchers with carefully detailed processes for collection of HS specimens would accelerate the accumulation of well-organized human biological material. Over time, the scientific community will have access to a broad range of HS tissue biospecimens, ultimately leading to more rigorous basic and translational research. Moreover, an improved understanding of the pathophysiology is necessary for the discovery of novel therapies for this debilitating disease. We aim to provide high impact translational research methodology for cutaneous biology research and foster multidisciplinary collaboration and advancement of our understanding of cutaneous diseases.
PMCID:6704132
PMID: 31434914
ISSN: 2045-2322
CID: 5710782
Dysregulation of antioxidant enzyme PRDX5 in alopecia areata [Meeting Abstract]
ISI:000482187300043
ISSN: 0022-202x
CID: 5713802
Genome-wide association study of acne inversa in a multi-ethnic cohort [Meeting Abstract]
ISI:000485661500002
ISSN: 0022-202x
CID: 5713792
FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications
We describe a method based on a latent Dirichlet allocation model for predicting functional effects of noncoding genetic variants in a cell-type- and/or tissue-specific way (FUN-LDA). Using this unsupervised approach, we predict tissue-specific functional effects for every position in the human genome in 127 different tissues and cell types. We demonstrate the usefulness of our predictions by using several validation experiments. Using eQTL data from several sources, including the GTEx project, Geuvadis project, and TwinsUK cohort, we show that eQTLs in specific tissues tend to be most enriched among the predicted functional variants in relevant tissues in Roadmap. We further show how these integrated functional scores can be used for (1) deriving the most likely cell or tissue type causally implicated for a complex trait by using summary statistics from genome-wide association studies and (2) estimating a tissue-based correlation matrix of various complex traits. We found large enrichment of heritability in functional components of relevant tissues for various complex traits, and FUN-LDA yielded higher enrichment estimates than existing methods. Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods. In particular, our results suggest that tissue- and cell-type-specific functional prediction methods tend to have substantially better prediction accuracy than organism-level prediction methods. Scores for each position in the human genome and for each ENCODE and Roadmap tissue are available online (see Web Resources).
PMCID:5986983
PMID: 29727691
ISSN: 1537-6605
CID: 5712332
Genome-Wide MicroRNA Analysis Implicates miR-30b/d in the Etiology of Alopecia Areata
Alopecia areata (AA) is one of the most common forms of human hair loss. Although genetic studies have implicated autoimmune processes in AA etiology, understanding of the etiopathogenesis is incomplete. Recent research has implicated microRNAs, a class of small noncoding RNAs, in diverse autoimmune diseases. To our knowledge, no study has investigated the role of microRNAs in AA. In this study, gene-based analyses were performed for microRNAs using data of the largest genome-wide association meta-analysis of AA to date. Nominally, significant P-values were obtained for 78 of the 617 investigated microRNAs. After correction for multiple testing, three of the 78 microRNAs remained significant. Of these, miR-30b/d was the most significant microRNA for the follow-up analyses, which also showed lower expression in the hair follicle of AA patients. Target gene analyses for the three microRNAs showed 42 significantly associated target genes. These included IL2RA, TNXB, and ERBB3, which had been identified as susceptibility loci in previous genome-wide association studies. Using luciferase assay, site-specific miR-30b regulation of the AA risk genes IL2RA, STX17, and TNXB was validated. This study implicates microRNAs in the pathogenesis of AA. This finding may facilitate the development of future treatment strategies.
PMID: 29080678
ISSN: 1523-1747
CID: 5710492
Journal of investigative dermatology symposium proceedings. 2018:19(1):S57-S61.DOI: 10.1016/j.jisp.2017.10.006
Big Data Reveal Insights into Alopecia Areata Comorbidities
Autoimmune diseases create a substantial burden of disease, and alopecia areata is among the more prevalent forms. Comorbidities are medical conditions that tend to occur together and may provide etiologic insights, suggest novel therapeutic strategies, and help patients and family members understand the risk of other health conditions. It is well established that having one autoimmune disease increases risk for others because of an underlying shared biology. Precision medicine initiatives are creating vast amounts of data that allow us to efficiently identify comorbidities. A survey across various datasets suggests that patients with autoimmune disease, and patients with alopecia areata in particular, may have comorbid neuropsychiatric and metabolic conditions.
PMCID:5862393
PMID: 29273109
ISSN: 1529-1774
CID: 5710512
Computational derivation of a molecular framework for hair follicle biology from disease genes
Knowledge about genetic drivers of disease increases the efficiency of interpreting patient DNA sequence and helps to identify and prioritize biological points of intervention. Discoveries of genes with single mutations exerting substantial phenotypic impact reliably provide new biological insight, although such approaches tend to generate knowledge that is disjointed from the complexity of biological systems governed by elaborate networks. Here we sought to facilitate diagnostic sequencing for hair disorders and assess the underlying biology by compiling an archive of 684 genes discovered in studies of monogenic disorders and identifying molecular annotations enriched by them. To demonstrate utility for this dataset, we performed two data driven analyses. First, we extracted and analyzed data implicating enriched signaling pathways and identified previously unrecognized contributions from Hippo signaling. Second, we performed hierarchical clustering on the entire dataset to investigate the underlying causal structure of hair disorders. We identified 35 gene clusters representing genetically derived biological modules that provide a foundation for the development of a new disease taxonomy grounded in biology, rather than clinical presentations alone. This Resource will be useful for diagnostic sequencing in patients with diseases affecting the hair follicle, improved characterization of hair follicle biology, and methods development in precision medicine.
PMCID:5701154
PMID: 29176608
ISSN: 2045-2322
CID: 5710502
Shedding Light on Alopecia Areata in Pediatrics: A Retrospective Analysis of Comorbidities in Children in the National Alopecia Areata Registry
Alopecia areata (AA) is a common autoimmune disease and it is challenging to predict which patients will have severe disease. The purpose of this retrospective study was to identify comorbidities in children enrolled in the National Alopecia Areata Registry. Atopic dermatitis was more common in patients with severe AA than in those with mild disease. The most common autoimmune comorbidities were vitiligo, psoriasis, thyroid disease, and juvenile idiopathic arthritis.
PMID: 28884897
ISSN: 1525-1470
CID: 5710482
Genomewide analysis of copy number variants in alopecia areata in a Central European cohort reveals association with MCHR2
Alopecia areata (AA) is a common hair loss disorder of autoimmune aetiology, which often results in pronounced psychological distress. Understanding of the pathophysiology of AA is increasing, due in part to recent genetic findings implicating common variants at several genetic loci. To date, no study has investigated the contribution of copy number variants (CNVs) to AA, a prominent class of genomic variants involved in other autoimmune disorders. Here, we report a genomewide- and a candidate gene-focused CNV analysis performed in a cohort of 585 patients with AA and 1340 controls of Central European origin. A nominally significant association with AA was found for CNVs in the following five chromosomal regions: 4q35.2, 6q16.3, 9p23, 16p12.1 and 20p12.1. The most promising finding was a 342.5-kb associated region in 6q16.3 (duplications in 4/585 patients; 0/1340 controls). The duplications spanned the genes MCHR2 and MCHR2-AS1, implicated in melanin-concentrating hormone (MCH) signalling. These genes have not been implicated in previous studies of AA pathogenesis. However, previous research has shown that MCHR2 affects the scale colour of barfin flounder fish via the induction of melanin aggregation. AA preferentially affects pigmented hairs, and the hair of patients with AA frequently shows a change in colour when it regrows following an acute episode of AA. This might indicate a relationship between AA, pigmentation and MCH signalling. In conclusion, the present results provide suggestive evidence for the involvement of duplications in MCHR2 in AA pathogenesis.
PMID: 27306922
ISSN: 1600-0625
CID: 5710452
Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study
IMPORTANCE/OBJECTIVE:The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. OBJECTIVE:To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. DATA SOURCES/METHODS:Genomewide association studies (GWAS) published up to January 15, 2015. STUDY SELECTION/METHODS:GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available. DATA EXTRACTION AND SYNTHESIS/METHODS:Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. MAIN OUTCOMES AND MEASURES/METHODS:Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. RESULTS:Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]). CONCLUSIONS AND RELEVANCE/CONCLUSIONS:It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.
PMID: 28241208
ISSN: 2374-2445
CID: 5710472
