A systematic simulation-based meta-analytical framework for prediction of physiological biomarkers in alopecia
JOURNAL OF BIOLOGICAL RESEARCH-THESSALONIKI
Authors: Muhammad, Syed Aun; Fatima, Nighat; Paracha, Rehan Zafar; Ali, Amjad; Chen, Jake Y.
Abstract
BackgroundAlopecia or hair loss is a complex polygenetic and psychologically devastating disease affecting millions of men and women globally. Since the gene annotation and environmental knowledge is limited for alopecia, a systematic analysis for the identification of candidate biomarkers is required that could provide potential therapeutic targets for hair loss therapy.ResultsWe designed an interactive framework to perform a meta-analytical study based on differential expression analysis, systems biology, and functional proteomic investigations. We analyzed eight publicly available microarray datasets and found 12 potential candidate biomarkers including three extracellular proteins from the list of differentially expressed genes with a p-value<0.05. After expression profiling and functional analysis, we studied protein-protein interactions and observed functional associations of source proteins including WIF1, SPON1, LYZ, GPRC5B, PTPRE, ZFP36L2, HBB, PHF15, LMCD1, KRT35 and VAV3 with target proteins including APCDD1, WNT1, WNT3A, SHH, ESRI, TGFB1, and APP. Pathway analysis of these molecules revealed their role in major physiological reactions including protein metabolism, signal transduction, WNT, BMP, EDA, NOTCH and SHH pathways. These pathways regulate hair growth, hair follicle differentiation, pigmentation, and morphogenesis. We studied the regulatory role of -catenin, Nf-kappa B, cytokines and retinoic acid in the development of hair growth. Therefore, the differential expression of these significant proteins would affect the normal level and could cause aberrations in hair growth.ConclusionOur integrative approach helps to prioritize the biomarkers that ultimately lessen the economic burden of experimental studies. It will also be valuable to discover mutants in genomic data in order to increase the identification of new biomarkers for similar problems.
Increased Frequency of De Novo Copy Number Variants in Congenital Heart Disease by Integrative Analysis of Single Nucleotide Polymorphism Array and Exome Sequence Data
CIRCULATION RESEARCH
Authors: Glessner, Joseph T.; Bick, Alexander G.; Ito, Kaoru; Homsy, Jason G.; Rodriguez-Murillo, Laura; Fromer, Menachem; Mazaika, Erica; Vardarajan, Badri; Italia, Michael; Leipzig, Jeremy; DePalma, Steven R.; Golhar, Ryan; Sanders, Stephan J.; Yamrom, Boris; Ronemus, Michael; Iossifov, Ivan; Willsey, A. Jeremy; State, Matthew W.; Kaltman, Jonathan R.; White, Peter S.; Shen, Yufeng; Warburton, Dorothy; Brueckner, Martina; Seidman, Christine; Goldmuntz, Elizabeth; Gelb, Bruce D.; Lifton, Richard; Seidman, Jonathan; Hakonarson, Hakon; Chung, Wendy K.
Abstract
Rationale: Congenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown pathogenesis. Objective: To determine the contribution of de novo copy number variants (CNVs) in the pathogenesis of sporadic CHD. Methods and Results: We studied 538 CHD trios using genome-wide dense single nucleotide polymorphism arrays and whole exome sequencing. Results were experimentally validated using digital droplet polymerase chain reaction. We compared validated CNVs in CHD cases with CNVs in 1301 healthy control trios. The 2 complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either single nucleotide polymorphism array (P=7x10(-5); odds ratio, 4.6) or whole exome sequencing data (P=6x10(-4); odds ratio, 3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (P=0.02; odds ratio, 2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in whole exome sequencing and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q subtelomeric deletions. Conclusions: We demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD.