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IDENTIFICATION OF COMMON UNDERLYING PATHOLOGIES ASSOCIATED WITH MALE

or Reprod er f uc nt ti e ve C M n a e c d AND DIABETES USING DATA MINING AND IN-SILICO FUNCTIONAL STUDIES i i r c

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C Narasimhan Kothandaraman, PhD , Ashok Agarwal, PhD , Mourad Assidi, MD , Muhammad Abu-Elmagd, MD 3 e 9 n 9 tr 1 um t. E Es 1American Center for Reproductive Medicine, Cleveland Clinic, Cleveland, Ohio xcellentiae 2Center for Excellence in Genomic Medicine Research, King Abdul Aziz University, Jeddah, Saudi Arabia

ABSTRACT RESULTS RESULTS RESULTS

Objective: Recent reports indicate men with diabetes have abnormal parameters, which could affect Data mining from published literature show men with diabetes present with a higher Table 1. Identification of 6 sets associated with proteasome, Table 3. Tissue specific expression from proteomics their fertility status. The objective of the current study was to evaluate the functional relevance of risk of infertility in the general population. For the current study diabetes associated and common to diabetes and those associated with by performing in-silico analysis. heat shock, hypoxia, growth differentiation, peptidase, proteins as well as spermatozoa and seminal plasma proteins from infertile patients DB (1-2) /human proteome map (3-4) analysis Study Design: The study considered all genes and proteins from published data representing infertility and diabetes and proteins reported from studies using seminal plasma and spermatozoa from patient with high, medium, and low ROS conditions were curated from literature databases. dehydrogenase and binding proteins. using tissue specific expression pattern of gene samples with high, medium and low levels of (ROS) in their semen samples. and proteins associated with infertility and Materials and Methods: Through datamining genes and the associated proteins they encode were identified 1. A total of 11,454 proteins were curated to be associated with the above Gene Group Gene Symbol Gene Name and used for further downstream in-silico analysis to identify functionalities associated with these common conditions (Figure 1). diabetes. set of genes and proteins. 2. Curation as well as filtering led to the listing of 202 common proteins to Gene Group 1 PSMB 1-7 proteasome (prosome, macropain) subunit, beta type, 3 Results: A total of 11,454 proteins representing (1) infertility, (2) diabetes, (3) proteins reported from studies diabetes and male infertility (proteins from spermatozoa and seminal Gene Group 2 using seminal plasma and spermatozoa from high, medium and low ROS in patient semen samples were LCN2 lipocalin 2 Source Tissue Overlap p-value Genes listed for the current study. Gene sets associated with oxidative phosphorylation, fatty acid metabolism, and plasma of patients with due to ROS). ORM1 orosomucoid 1 ROS pathways were more represented in the gene sets common to these two diseases. Tissue localization 3. Forty-five genes were cytoplasmic in origin. TMEFF2;SMPD; FAM3B family with sequence similarity 3, member B analysis showed majority of genes ( surface receptors, TFs, translocated genes) were localized in adult 4. 6 gene sets were identified and are shown in (Table 1). Proteomics DB Seminal 0.06847 GNAS;KLK2; and testis. Functional annotation of listed genes using DAVID showed acetylation, proteinase and 5. Metabolism and stress pathway associated genes are shown in Table 2. GDF15 growth differentiation factor 15 (1) plasma 6/301 6159 ALOX15B; hydrolase to be overrepresented. metabolism, PTM, cytoskeleton and signal transduction mechanisms PLA2G7 share common ground with the two pathologies. Unique findings of the current study include MTORC1 6. Tissue localization analysis identified genes present in seminal plasma, Gene Group 3 HYOU1 hypoxia upregulated 1 signaling and MYC regulation as common pathways to both male infertility and diabetes conditions. Other , adult prostate and testis (Table 3). TCP1 hypothetical gene supported by BC000665; t-complex 1 0.45545 ACTL7A; pathway proteins that were overrepresented common to both disease conditions include genes associated 7. The major biological process are shown in Table 4. Oxidoreductase, peptidase (2) Spermatozoon 2/301 8122 KLK2 with lipid metabolism (PPARA), extracellular matrix proteoglycans and inhibition of E2F mediated cell cycle CKB , brain regulation. On further research into individual target lists showed their role in and and calcium binding were the prominent molecular function associated maturation, and recognition. The common genes play major role in metabolism of proteins. Functional analyses showed acetylation, ROS, proteinase and HSPA2 heat shock 70kDa protein 2 Human Proteome 0.21297 Adult prostate 1/301 SLPI and lipoproteins, testicular atrophy and affect capacitation, reaction, and of ejaculated Map (3) 8949 hydrolase being significantly overrepresented. HSPA1A, HSPA1B heat shock 70kDa protein 1A; heat shock 70kDa protein 1B human sperm. 8. Lipid metabolism, post-translational modification (PTM) genes, (TPP1, Conclusions: The study shows commonalties between diabetes and infertility at the molecular level. The hypothetical protein FLJ11822; 0.21297 results from this study will help in providing early leads to explain why people with diabetics have a higher PRDX6), cytoskeleton and signal transduction genes were functionally Gene Group 4 NPEPPS (4) Adult testis 1/301 LYZL4 aminopeptidase puromycin sensitive 8949 chance to acquiring infertility later in life. relevant in the common set of genes associated with DM and sperm/seminal plasma under OS identified using functional annotation CPE carboxypeptidase E studies using DAVID open source annotation package. CPD carboxypeptidase D INTRODUCTION 9. Overrepresented entities of metabolic pathways include those associated with energy metabolism such as glycolysis, gluconeogenesis, pentose CNDP2 CNDP dipeptidase 2 (metallopeptidase M20 family) It is found that both infertility and diabetes share common underlying pathologies. phosphate pathway (PPP), fatty acid beta-oxidation. These pathways are CPM carboxypeptidase M It is plausible that a history of diabetes could often result in infertility over a period Table 4. Identification of genes associated with biological well characterized and associated with various impairments of sperm Gene Group 5 HADH hydroxyacyl-Coenzyme A dehydrogenase of time. Prospective cohort studies show that the inverse is also true where a long associated disorders. processes or biological functions. ACADM duration of infertility could lead to the development of chronic diseases as diabetes 10. Metabolic analysis showed genes/proteins associated with glycolysis, acyl-Coenzyme A dehydrogenase, C-4 to C-12 straight chain later in life. Being a metabolic disorder, diabetes presents with this unique opportunity gluconeogenesis, pentose phosphate pathway and fatty acid beta-oxidation ECH1 enoyl Coenzyme A hydratase 1, peroxisomal No. Gene Set Name Genes p-value Gene Gene Description to investigate the key metabolic alterations that could result in the aberrations as well among the top 4 metabolically active in the genes set representation, which IVD isovaleryl Coenzyme A dehydrogenase superoxide as proteome changes in human spermatozoid as well as the seminal fluid which correlates with the catabolic process acting in the OD rich environment. RESPONSE could facilitate the assessment of fertility of the affected individual. We hypothesize ACADS acyl-Coenzyme A dehydrogenase, C-2 to C-3 short chain 1 25 4.56E-19 SOD1 dismutase 1, 11. Four target pathways were identified which could further investigated for TO STRESS soluble that seminal fluid and spermatozoid proteome of infertile men with diabetes show their biological role in mediating diabetes-associated infertility in males. ACADVL acyl-Coenzyme A dehydrogenase, very long chain unique proteomic fingerprints, which could help to identify diabetes associated These include: Gene Group 6 S100A9 S100 calcium binding protein A9 heat shock infertility markers in males. In this preliminary study we propose to identify REGULATION S100 calcium binding protein A11; S100 calcium 2 21 3.84E-18 HSPA1B 70kDa protein proteins or network of proteins and key pathways that are associated with infertility I. Androgen dependent RAF/MAP kinase signaling pathway cascade S100A11 OF binding protein A11 pseudogene 1B in men presenting with diabetes from a global perspective using proteomics II. Peroxisome proliferator-activated receptor alpha (PPARA) which is approach. The outcome from the proposed project will have implications in the responsible for metabolism of lipids, fatty acids and lipoproteins. PPARA also PLS3 plastin 3 (T isoform) REGULATION OF valosin management of infertile patients posing with other chronic disease conditions has known effects in causing sensitization to insulin and play a key role in 3 PROGRAMMED 21 4.08E-18 VCP containing S100A8 S100 calcium binding protein A8 CELL DEATH protein sharing similar pathologies. A better understanding of the underlying mechanisms sperm capacitation, motility and could also cause atrophy in testis would help in prioritizing treatment options for such men were infertility could be III. pathways associated with ECM remodeling through Rho (Role: is required 4 APOPTOSIS GO 22 3.13E-17 ANXA1 annexin A1 reversed through suitable pharmacological interventions. We hypothesized patients for successful fertilization and sperm penetration) with diabetes and infertile patients with no known etiology of chronic diseases but IV. E2F enabled inhibition of pre-replication complex formation. Ubiquitous REGULATION OF categorized under those presenting with high, medium and low ROS in spermatozoa expression of E2F in all testes cell types and tissues are reported in Table 2. Identification of gene sets associated with metabolism 6 DEVELOPMENTAL 22 4.82E-17 MPO myeloperoxidase and seminal plasma share common underlying regulatory mechanism since both models in response to endocrine disruptors. E2F mediated and stress PROCESS diabetes and infertility show similar pathophysiology. regulation of DNA replication genes include MCM8, PPP2R1A, ORC3L. CELL V. It is evident from these results that diabetes-inflicted infertility might # Genes in 7 1.08E-16 PRDX2 peroxiredoxin 2 No. Gene Set Description p-value DEVELOPMENT 24 share a huge array of genes and proteins that might accelerate the Overlap (k) MATERIALS and METHODS signaling cascade associated with different pathways common to both Genes encoding components of the CELLULAR heat shock protein diseases. Results from this study show diabetes share similar association 1 COMPLEMENT 21/200 complement system, which is part 5.57E-23 8 CATABOLIC 16 1.76E-15 HSP90B1 90kDa beta (Grp94), We conducted a preliminary study to investigate the underlying phenotype of infertility between infertility associated genes. It is confident to say that both share of the innate immune system. PROCESS member 1 and diabetes, which share similar pathophysiology. Towards this objective we conducted a common platform in many disease pathways leading to infertility. Genes up-regulated through 2 MTORC1 SIGNALING 19/200 4.65E-20 CATABOLIC heat shock 70kDa an in silico study on data available from recent published papers describing the It remains to be investigated if infertility in the presence of diabetes activation of mTORC1 complex. 9 PROCESS 16 4.49E-15 HSPA2 protein 2 identification of proteins using MS techniques. A comprehensive literature search aggravates the severity of the affected pathways and networks thereby A subgroup of genes regulated (from PUBMED, SCOPUS and Medline) as well as data mining of published literature 3 MYC TARGETS_V1 18/200 1.23E-18 LIPID METABOLIC causing irreparable damage to the process of spermatogenesis. by MYC - version 1 (v1). 10 18 6.52E-15 PRDX6 PRDX6 resulted in the indication of more than 6000 proteins associated with infertility PROCESS OXIDATIVE Genes encoding proteins involved and more than 1000 proteins in seminal plasma. Using the same mining tools we 4 3.03E-17 PHOSPHORYLATION 17/200 in oxidative phosphorylation. identified a total of 6035 genes/proteins from various published studies associated Figure 1 Genes encoding proteins involved with Diabetes. Majority of the reports indicate ROS induced OS as the common Diabetes Sperm ROS 5 FATTY ACID METABOLISM 15/200 4.42E-16 underlying pathologies in both diabetes as well as infertility. in metabolism of fatty acids. Venn diagram representing 4120 106 Genes up-regulated in response (39.1%) (1%) common and unique 6 HYPOXIA 16/200 to low oxygen levels (hypoxia). 6.99E-16 Once the data mining and curation were completed, the following categories of proteins proteins corresponding 1358 20 84 were sorted individually for further downstream analysis: 1) common proteins to (0.2%) to diabetes-associated Genes encoding components of (12.9%) (0.8%) CONCLUSIONS diabetes, 2) proteins reported for infertility in males, 3) proteins reported for sperm proteins, data-mined 7 COAGULATION 14/138 blood coagulation system; also 1.69E-15 3359 67 proteins associated with producing high, medium and low ROS, and 4) seminal plasma proteins from patients (31.8%) 245 13 (0.6%) up-regulated in platelets. (2.3%) (0.1%) producing high, medium and low ROS. These four classes of proteins were further male infertility, spermatozoa 1. People with diabetes have a higher chance of acquiring infertility later in life. and seminal plasma Genes up-regulated during adipocyte merged to identify common set of proteins. Through this study for the first time 189 8 ADIPOGENESIS 15/200 differentiation (adipogenesis). 1.50E-14 (1.8%) proteins identified under we have narrowed down the genes encoding proteins that share the same space 535 36 2. Identification of unique proteomic signature in patients with diabetes could (5.1%) (0.3%) high, medium and low Genes encoding proteins involved 276 53 ROS conditions. lead to early detection of infertility. in the both disease conditions. A total of 202 genes and associated proteins they code (2.6%) (0.5%) 9 GLYCOLYSIS 14/200 in glycolysis and gluconeogenesis. 2.99E-13 were identified using filtering approaches which were used for further downstream 87 Infertility (0.8%) Seminal Plasma ROS REACTIVE OXYGEN Genes up-regulated by reactive in silico analysis to identify functionalities associated with these common set of genes 10 7.89E-13 3. Understanding these factors may help in planning personalized treatment SPECIES PATHWAY 9/49 oxigen species (ROS). and proteins which could provide leads for further detailed downstream functional studies. modalities for these categories of patients.