Human Genome Epidemiology Research Articles

Bioinformatic approach for repurposing immunomodulatory drugs for lepromatous leprosy.

The lepromatous leprosy (LL) disease is caused by Mycobacterium leprae and Mycobacterium lepromatosis which is characterized by inadequate response to treatment, a propensity to drug resistance, and patient disability. We aimed to evaluate current immunomodulatory medicines and their target proteins collectively as a drug repurposing strategy to decipher novel uses for LL. A dataset of human genes associated with LL-immune response was retrieved from public health genomic databases including the Human Genome Epidemiology Navigator and DisGeNET. Retrieved genes were filtered and enriched to set a robust network (≥10, up to 21 edges) and analyzed in the Cytoscape program (v3.9). Drug associations were obtained in the NDEx Integrated Query (v1.3.1) coupled with drug databases such as ChEMBL, BioGRID, and DrugBank. These networks were analyzed in Cytoscape with the CyNDEx-2 plugin and STRING protein network database. Pathways analyses resulted in 100 candidate drugs organized into pharmacological groups with similar targets and filtered on 54 different drugs. Gene-target network analysis showed that the main druggable targets associated with LL were tumoral necrosis factor-alpha, interleukin-1B, and interferon-gamma. Consistently, glucosamine, binimetinib, talmapimod, dilmapimod, andrographolide, and VX-702 might have a possible beneficial effect coupled with LL treatment. Based on our drug repurposing analysis, immunomodulatory drugs might have a promising potential to be explored further as therapeutic options or to alleviate symptoms in LL patients.

Integrative analyses of genes about venous thromboembolism: An umbrella review of systematic reviews and meta-analyses.

In recent years, many studies have found possible links between gene polymorphisms and venous thromboembolism (VTE). By identifying genetic risk factors before facing environmental risk factors such as surgical interventions and COVID-19 vaccination, we could rapidly respond to the risk of VTE. The aim of this study was to perform an umbrella review of genetic variants related to VTE. Integrative gene analysis of VTE was performed to identify critical genetic variations. This study conducted an umbrella review of systematic reviews and meta-analyses. All included studies were selected from the PubMed/MEDLINE database. To select eligible studies, the following variables were extracted: first author name; effect size of each study genetic variant; year of publication; the number of studies included in each article; ethnicity, sample size, P values, and heterogeneity estimates. To assess cumulative evidence in genetic epidemiology about effects of gene polymorphisms on VTE, Human Genome Epidemiology Network's Venice criteria were used. Methodological quality assessment was conducted with JBI Critical Appraisal Checklist for Systematic Reviews and Research Syntheses. Genes provided in the present study with genetic variants associated with VTE were FVL (G1691A), Prothrombin (G20210A), MTHFR (C677T, A1298C), PAI-1 (4G/5G), factor VII activating protease (1601G > A), and endothelial protein C receptor (g.6936A_G, c.4600A_G). Among them, variants in FVL, Prothrombin, MTHFR, and PAI-1 showed high significance. Particularly, variants in Prothrombin (G20210A), MTHFR (C677T), and PAI-1 (4G/5G) had more than 2 types of model significance. The present study performed a systematic review of genetic variants associated with VTE. Our results could lead to a more comprehensive understanding of VTE etiology. These results could give a strategy of prediagnosis about evaluating individual risks of VTE who might be exposed to environmental risk factors.

Methylenetetrahydrofolate Reductase Polymorphism (rs1801133) and the Risk of Hypertension among African Populations: A Narrative Synthesis of Literature.

In this review, we have gathered and analyzed the available genetic evidence on the association between the methylenetetrahydrofolate reductase gene (MTHFR), rs1801133 and the risk of Hypertension (HTN) in African populations, which was further compared to the global data evidence. This review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol and Human Genome Epidemiology Network (HuGENet) guidelines. Literature was retrieved through major search databases, including PubMed, Scopus, Web of Science, and African Journal Online. We identified 64 potential studies, of which 4 studies were from the African continent and 60 studies were reported globally. Among the studies conducted in Africa, only two (n = 2) reported a significant association between the MTHFR (rs1801133) and the risk of developing HTN. Only one (n = 1) study population was purely composed of black Africans, while others were of other ethnicities. Among studies conducted in other continents (n = 60), forty-seven (n = 47) studies reported a positive association between MTHFR (rs1801133) and the risk of developing HTN, whereas the remaining studies (n = 14) did not show a significant association. Available literature suggests an apparent association between rs1801133 and HTN in global regions; however, such information is still scarce in Africa, especially in the black African population.

Synthesis of genetic association studies on autism spectrum disorders using a genetic model-free approach.

Autism spectrum disorder (ASD) is a clinically and genetically heterogeneous group of neurodevelopmental disorders. Despite the extensive efforts of scientists, the etiology of ASD is far from completely elucidated. In an effort to enlighten the genetic architecture of ASDs, a meta-analysis of all available genetic association studies (GAS) was conducted. We searched in the Human Genome Epidemiology Navigator (HuGE Navigator) and PubMed for available case-control GAS of ASDs. The threshold for meta-analysis was two studies per genetic variant. The association between genotype distribution and ASDs was examined using the generalized linear odds ratio (ORG). For variants with available allele frequencies, the examined model was the allele contrast. Overall, 57 candidate genes and 128 polymorphisms were investigated in 159 articles. In total 28 genetic polymorphisms have been shown to be associated with ASDs, that are harbored in 19 genes. Statistically significant results were revealed for the variants of the following genes adenosine deaminase (ADA), bone marrow stromal cell antigen-1 (CD157/BST1), Dopamine receptor D1 (DRD1), engrailed homolog 2 (EN2), met proto-oncogene (MET), methylenetetrahydrofolate reductase (MTHFR), solute carrier family 6 member 4 (SLC6A4), Synaptosomal-associated protein, 25kDa (SNAP-25) and vitamin D receptor (VDR). In the allele contrast model of cases versus healthy controls, significant associations were observed for Adrenoceptor Alpha 1B (ADRA1B), acetyl serotonin O - methyltransferase (ASMT), complement component 4B (C4B), dopamine receptor D3 (DRD3), met proto-oncogene (MET), neuroligin 4, X-linked (NLGN4), neurexin 1 (NRXN1), oxytocin receptor (OXTR), Serine/Threonine-Protein Kinase PFTAIRE-1 (PFTK1), Reelin (RELN) and Ras-like without CAAX 2 (RIT2). These significant findings provide further evidence for genetic factors' implication in ASDs offering new perspectives in means of prevention and prognosis.

Role of CGRP pathway polymorphisms in migraine: a systematic review and impact on CGRP mAbs migraine therapy

Backgroundthe interest of clinical reaseach in polymorphisms and epigenetics in migraine has been growing over the years. Due to the new era of preventative migraine treatment opened by monoclonal antibodies (mAbs) targeting the signaling of the calcitonin-gene related peptide (CGRP), the present systematic review aims at identifying genetic variants occurring along the CGRP pathway and at verifying whether these can affect the clinical features and the course of disease and the responsiveness of patients to therapy.Methodsthe literature search has been conducted consulting the most relevant scientific databases, i.e. PubMed/MEDLINE, Scopus, Web of Science, the Human Genome Epidemiology (HuGE) Published Literature database (Public Health Genomics Knowledge Base) and Clinicaltrials.gov from database inception until April 1, 2021. The process of identification and selection of the studies included in the analysis has followed the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) criteria for systematic reviews and meta-analyses and the guidance from the Human Genome Epidemiology Network for reporting gene-disease associations.Resultsthe search has retrieved 800 results, among which only 7 studies have met the eligibility criteria for inclusion in the analysis. The latter are case-control studies of genetic association and an exploratory analysis and two polymorphisms have been detected as the most recurring: the rs3781719 (T > C) of the CALC A gene encoding CGRP and the rs7590387 of the gene encoding the receptor activity-modifying protein (RAMP) 1 (C > G). Only one study assessing the methylation pattern with regard to CGRP pathway has been found from the search. No genetic association studies investigating the possible effect of genetic variants affecting CGRP signaling on the responsiveness to the most recent pharmacological approaches, i.e. anti-CGRP(R) mAbs, gepants and ditans, have been published. According to the Human Genome Epidemiology (HuGE) systematic reviews and meta-analyses risk-of-bias score for genetic association studies, the heterogeneity between and across studies and the small sample size do not allow to draw conclusions and prompt future studies.Conclusionsadequately powered, good quality genetic association studies are needed to understand the impact of genetic variants affecting the pathway of CGRP on migraine susceptibility and clinical manifestation and to predict the response to therapy in terms of efficacy and safety.

The genetic map of diabetic nephropathy: evidence from a systematic review and meta-analysis of genetic association studies.

Despite the extensive efforts of scientists, the genetic background of diabetic nephropathy (DN) has not yet been clarified. To elucidate the genetic variants that predispose to the development of DN, we conducted a systematic review and meta-analysis of all available genetic association studies (GAS) of DN. We searched in the Human Genome Epidemiology Navigator (HuGE Navigator) and PubMed for available GAS of DN. The threshold for meta-analysis was three studies per genetic variant. The association between genotype distribution and DN was examined using the generalized linear odds ratio (ORG). For variants with available allele frequencies, the examined model was the allele contrast. The pooled OR was estimated using the DerSimonian and Laird random effects model. The publication bias was assessed with Egger’s test. We performed pathway analysis of significant genes with DAVID 6.7. Genetic data of 606 variants located in 228 genes were retrieved from 360 GASs and were synthesized with meta-analytic methods. ACACB, angiotensin I-converting enzyme (ACE), ADIPOQ, AGT, AGTR1, AKR1B1, APOC1, APOE, ATP1B2, ATP2A3, CARS, CCR5, CGNL1, Carnosine dipeptidase 1 (CNDP1), CYGB-PRCD, EDN1, Engulfment and cell motility 1 (ELMO1), ENPP1, EPO, FLT4, FTO, GLO1, HMGA2, IGF2/INS/TH cluster, interleukin 1B (IL1B), IL8, IL10, KCNQ1, KNG, LOC101927627, Methylenetetrahydrofolate reductase, nitric oxide synthase 3 (NOS3), SET domain containing seven, histone lysine methyltransferase (SETD7), Sirtuin 1 (SIRT1), SLC2A1, SLC2A2, SLC12A3, SLC19A3, TCF7L2, TGFB1, TIMP1, TTC39C, UNC13B, VEGFA, WTAPP1, WWC1 as well as XYLT1 and three intergenic polymorphisms showed significant association with DN. Pathway analysis revealed the overrepresentation of six signalling pathways. The significant findings provide further evidence for genetic factors implication in DN offering new perspectives in discovery of new therapies.

What is the evidence for interactions between filaggrin null mutations and environmental exposures in the aetiology of atopic dermatitis? A systematic review.

SummaryBackgroundEpidemiological studies indicate that gene–environment interactions play a role in atopic dermatitis (AD).ObjectivesTo review the evidence for gene–environment interactions in AD aetiology, focusing on filaggrin (FLG) loss‐of‐function mutations.MethodsA systematic search from inception to September 2018 in Embase, MEDLINE and BIOSIS was performed. Search terms included all synonyms for AD and filaggrin/FLG; any genetic or epidemiological study design using any statistical methods were included. Quality assessment using criteria modified from guidance (ROBINS‐I and Human Genome Epidemiology Network) for nonrandomized and genetic studies was completed, including consideration of power. Heterogeneity of study design and analyses precluded the use of meta‐analysis.ResultsOf 1817 papers identified, 12 studies fulfilled the inclusion criteria required and performed formal interaction testing. There was some evidence for FLG–environment interactions in six of the studies (P‐value for interaction ≤ 0·05), including early‐life cat ownership, older siblings, water hardness, phthalate exposure, higher urinary phthalate metabolite levels (which all increased AD risk additional to FLG null genotype) and prolonged breastfeeding (which decreased AD risk in the context of FLG null genotype). Major limitations of published studies were the low numbers of individuals (ranging from five to 94) with AD and FLG loss‐of‐function mutations and exposure to specific environmental factors, and variation in exposure definitions.ConclusionsEvidence on FLG–environment interactions in AD aetiology is limited. However, many of the studies lacked large enough sample sizes to assess these interactions fully. Further research is needed with larger sample sizes and clearly defined exposure assessment. Linked Comment: Park and Seo. Br J Dermatol 2020; 183:411.

From human genome epidemiology to systems epidemiology: current progress and future perspective.

The recent progress in human genome epidemiology (HuGE) is already having a profound impact on the practice of medicine and public health. First, the success of genome-wide association studies has greatly expanded the direction and content of epidemiological researches, including revealing new genetic mechanisms of complex diseases, identifying new targets for therapeutic interventions, and improving application in early screening of high-risk populations. At the same time, large-scale genomic studies make it possible to efficiently explore the gene-environment interactions, which will help better understand the biological pathways of complex diseases and identify individuals who may be more susceptible to diseases. Additionally, the emergence of systems epidemiology aims to integrate multi-omics together with epidemiological data to create a systems network that can comprehensively characterize the diverse range of factors contributing to disease development. These progress will help to apply HuGE findings into practice to improve the health of individuals and populations.

Genetic and Non-Genetic Risk Factors for Gastric Cancer: A Field Synopsis and Evidence from 934 Chinese Population Studies

Background: China is one of the regions with the highest incidence, prevalence and mortality of gastric cancer worldwide. Yet, only few field synopses about non-genetic factors and genetic susceptibility in gastric carcinogenesis. The aim of this study is to summarize and assess the credibility and strength of non-genetic factors and genetic variation on the risk of gastric cancer. Methods: We used Chinese and international public databases to identify published studies that assessed associations between non-genetic factors and variants on candidate genes and the risk of gastric cancer in Chinese population. Cumulative epidemiological evidence of statistical relation was evaluate combining Venice criteria, a false-positive report probability (FPRP) test, attributable risk percentage (ARP) and population attributable risk percentage (PARP). Findings: A total of 622 articles (n=394 articles, 399 studies for non-genetic factors; n=532 articles, 535 studies for genetic factors) eligible articles were included in qualitative synthesis. A total of 16 common potential risk factors were extracted for non-genetic factors, and data on 1121 single nucleotide polymorphism (SNP) involving 441 distinct genes were available. We identified 14 non-genetic factors were significantly associated with gastric cancer risk: H. pylori infection, smoking, drinking, family history, stomach disease, high salt diet, pickled food, fast eating, irregular meals, edible hot food, smoked & frying, spicy diet, mental depression and diabetes. Meanwhile 22 variants were identified significantly associated with gastric cancer: 3 (PLCE1 rs2274223, PSCA rs2976392, MUC1 rs4072037) was high and 19 (MTHFR rs1801133, COX-2 rs20417, XRCC1 rs1799782 and rs25487, XRCC3, rs861539, NAT2 rs1799930 and rs1799929, PLCE1 rs3765524, GSTM1, GSTT1, IL-17A rs2275913 and rs8193036, PSCA rs2294008, PRKAA1 rs13361707, ERCC5 rs751402, TGFBR2 rs3773651, IL-10 rs1800896 and VDR rs731236) was intermediate level of summary evidence, respectively. As we add more non-genetic factors or susceptible genes to the model, the risk distribution expands, and the population can better distinguish high-risk and low-risk categories. For non-genetic factors, the top three for ARP were 66.33% (stomach disease), 54.34% (pickled food), and 49.75% (Smoked & frying). For PARP were 33.85% (pickled food), 24.73% (edible hot food) and 23.30% (H. pylori infection). On the basis of ARP and PARP associated with SNPs of gastric cancer, the top three for ARP were 53.91% (NAT2, rs1799929),53.05% (NAT2 phenotype), and 42.85% (IL-10, rs1800896). For PARP (CHB) were. 36.96% (VDR, rs731236), 25.58% (TGFBR2, rs3773651) and 20.56% (MUC1, rs4072037). Interpretation: We conducted the first field synopsis in Chinese population linking common non-genetic risk factors and DNA variation to summarize potential non-genetic and genetic risk factors for gastric cancer, and evaluate epidemiological indicators to identified high-quality biomarkers of gastric cancer. Our study provides referenced information for the non-genetic and genetic predisposition to gastric cancer. Funding Statement: This work was funded by the National Natural Science Foundation of China (81373097), Health Science and Technology Innovative Talents Project of Henan Province 2017, and Henan Medical Science and Technique Foundation (Co-sponsored by Province and Ministry, 2019). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study was conducted based on the Meta-analysis of Observational Studies in Epidemiology (MOOSE), Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and the systematic review principles of molecular association studies proposed by the Human Genome Epidemiology Network (HuGENet).

Tracking human genes along the translational continuum

Understanding the drivers of research on human genes is a critical component to success of translation efforts of genomics into medicine and public health. Using publicly available curated online databases we sought to identify specific genes that are featured in translational genetic research in comparison to all genomics research publications. Articles in the CDC’s Public Health Genomics and Precision Health Knowledge Base were stratified into studies that have moved beyond basic research to population and clinical epidemiologic studies (T1: clinical and population human genome epidemiology research), and studies that evaluate, implement, and assess impact of genes in clinical and public health areas (T2+: beyond bench to bedside). We examined gene counts and numbers of publications within these phases of translation in comparison to all genes from Medline. We are able to highlight those genes that are moving from basic research to clinical and public health translational research, namely in cancer and a few genetic diseases with high penetrance and clinical actionability. Identifying human genes of translational value is an important step towards determining an evidence-based trajectory of the human genome in clinical and public health practice over time.

HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity: a systematic review and meta-analysis.

Associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity have been reported. To consolidate the results from all available reports in scientific databases, systematic review and meta-analysis techniques were used to quantify these associations. Studies investigating associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity were systematically searched in PubMed, Human Genome Epidemiology Network, and the Cochrane Library. Primary outcomes were the associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity. Overall odds ratios (ORs) with the corresponding 95%CIs were calculated using a random-effect model to determine the associations between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity. A clear association between HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity was identified in our analyses. The summary OR was 6.23 (95%CI = 4.11-9.45). Similar associations were also found in the subgroup analyses by lapatinib treatment regimens. ORs were 10.04 (95%CI = 6.15-16.39), 8.65 (95%CI = 4.52-16.58), and 3.88 (95%CI = 2.20-6.82) in the lapatinib group, lapatinib + trastuzumab group, and lapatinib + chemotherapy or lapatinib + trastuzumab + chemotherapy group, respectively. Since HLA-DRB1*07:01 is associated with lapatinib-induced hepatotoxicity, genetic screening of HLA-DRB1*07:01 in breast cancer patients prior to lapatinib therapy is warranted for patient safety. In addition, further studies should define the risk of HLA-DRB1*07:01 and lapatinib-induced hepatotoxicity in specific ethnicities.

The Genetic Architecture of Tuberculosis Susceptibility: Comprehensive Research Synopsis, Meta-Analysis, and Epidemiological Evidence

Background: Over the past several decades, hundreds of genetic studies have been conducted to investigate associations between variants and risk of tuberculosis. But results have been inconclusive and no comprehensive quantitative synopsis has been available. We aimed to provide a summary of the current understanding of the genetic architecture of tuberculosis susceptibility. Methods: We systematically searched PubMed, Embase and Web of Science to identify genetic association studies of tuberculosis published through October 16, 2018. We did a meta-analysis for genetic variants with at least three independent datasets. We graded levels of cumulative epidemiological evidence of significant associations with risk of tuberculosis using the guidelines proposed by the Human Genome Epidemiology Network and false-positive report probability tests. We performed functional annotations for these variants using data from the Encyclopedia of DNA Elements (ENCODE) Project and other databases. Findings: We identified 592 eligible articles comprising 250431 cases with tuberculosis and 698635 controls without this disease through screening a total of 21330 citations. Meta-analysis-analyses were done for 580 variants in 314 genes or loci. We found that 37 variants were nominally significantly associated with risk of tuberculosis. Cumulative epidemiological evidence for a significant association with risk of tuberculosis was graded strong for 12 variants in or near 12 genes. Data from the ENCODE and other databases suggested that 10 of the 12 variants with strong evidence and those correlated with them might fall within putative functional regions. These variants together explained approximately 15.82% of familial relative risk of tuberculosis. Interpretation: Our study summarizes current literature on the genetic architecture of tuberculosis susceptibility and provides useful data for designing future studies to investigate new genetic factors for risk of tuberculosis. Funding Statement: This research is supported by grants from National Natural Science Foundation of China 81472026, 81672095, 81702288, 81673255, 81874283, the Projects of the Health and family planning commission in Sichuan Province 16ZD004, China Postdoctoral Science Foundation Project 2018M643495, the Recruitment Program for Young Professionals of China, Army Medical University WX2015-013, Army Medical University First Affiliated Hospital SWH2015LC03, SWH2016ZDCX1012, SWH2016JQFY-02, and SWH2015QN11, Chongqing Special Postdoctoral Science Foundation XmT2018068. Declaration of Interests: The authors declared no conflicts of interest. Ethics Approval Statement: We conducted this study in accordance with the guidelines of the Human Genome Epidemiology Network (HuGENet) for systematic review of genetic association studies and the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) Statement.

Gene-environment interactions and colorectal cancer risk: An umbrella review of systematic reviews and meta-analyses of observational studies.

The cause of colorectal cancer (CRC) is multifactorial, involving both genetic variants and environmental risk factors. We systematically searched the MEDLINE, EMBASE, China National Knowledge Infrastructure (CNKI) and Wanfang databases from inception to December 2016, to identify systematic reviews and meta‐analyses of observational studies that investigated gene–environment (G×E) interactions in CRC risk. Then, we critically evaluated the cumulative evidence for the G×E interactions using an extension of the Human Genome Epidemiology Network's Venice criteria. Overall, 15 articles reporting systematic reviews of observational studies on 89 G×E interactions, 20 articles reporting meta‐analyses of candidate gene‐ or single‐nucleotide polymorphism‐based studies on 521 G×E interactions, and 8 articles reporting 33 genome‐wide G×E interaction analyses were identified. On the basis of prior and observed scores, only the interaction between rs6983267 (8q24) and aspirin use was found to have a moderate overall credibility score as well as main genetic and environmental effects. Though 5 other interactions were also found to have moderate evidence, these interaction effects were tenuous due to the lack of main genetic effects and/or environmental effects. We did not find highly convincing evidence for any interactions, but several associations were found to have moderate strength of evidence. Our conclusions are based on application of the Venice criteria which were designed to provide a conservative assessment of G×E interactions and thus do not include an evaluation of biological plausibility of an observed joint effect.

A Systematic Review of Genetic Influence on Psychological Resilience.

When exposed to adversity, some individuals are at an increased risk of posttraumatic stress disorder, experiencing persistent biopsychosocial disturbances, whereas others adapt well, described as resilience. Resilience is a complex biopsychosocial phenomenon conceptualized as adaptation to adversity influenced by an individual's genetic variants, epistasis, epigenetics, and gene-by-environment interactions. Studies on psychological resilience have focused on behavioral and psychosocial variables with far less examination of the genetic contributions. The purpose of this review is to identify specific genetic variants contributing to the biological capacity for psychological resilience. PubMed and PsycINFO were searched using the following key words: psychological resilience AND genotype(s). Additional articles were identified from the Human Genome Epidemiology Navigator using the term resilience, psychological. Ten studies met the criteria. Six genes were empirically associated with psychological resilience: serotonin-transporter-linked polymorphic region ( 5-HTTLPR), dopamine receptor D4, brain-derived neurotrophic factor ( BDNF), corticotropin-releasing hormone receptor 1, oxytocin receptor and regulator of G-protein signaling 2 . The findings of this systematic review suggest that the L/L or L'/L' genotype of 5-HTTLPR and rs25531 in children/adolescents and the S/S or S'/S' genotype in adults are most frequently related to resilience. Additionally, the Val/Val genotype of rs6265 in BDNF in Caucasians was also associated with resilience. There are numerous factors contributing to the complexity of determining the genetic influence on resilience including analysis of rs25531, assumptions of the mode of inheritance, operationalization of resilience, demographic and population characteristics, sample size, and other types of genetic influence including epistasis and epigenetics. While current evidence is supportive, further investigation of the genetic influence on resilience is required.

Association Between HLA-B*1301 and Dapsone-Induced Cutaneous Adverse Drug Reactions

Dapsone-induced hypersensitivity syndrome (DHS) is a life-threatening adverse drug reaction. Based on available epidemiologic studies, HLA genotypes may play an important role in DHS. To assess the association between HLA-B*1301 and dapsone-induced cutaneous adverse drug reactions (cADRs). Human studies investigating associations between HLA-B*1301 and dapsone-induced cADRs were systematically searched without language restriction from the inception of each database until September 12, 2017, in PubMed, the Human Genome Epidemiology Network), and the Cochrane Library. Combinations of HLA genotypes, dapsone, and synonymous terms were used; reference lists were searched in selected articles. Two reviewers identified studies investigating the associations between HLA-B*1301 and dapsone-induced cADRs that reported sufficient data for calculating the frequency of HLA-B*1301 carriers among case and control patients, in which all patients received dapsone before HLA-B*1301 screening. An initial search of the databases identified 391 articles, of which 3 studies (2 in Chinese populations and 1 in a Thai population) met the inclusion criteria. Overall odds ratios (ORs) with 95% CIs were calculated using a random-effects model to determine the association between HLA-B*1301 and dapsone-induced cADRs. Subgroup analyses by type of cADR were also performed. PRISMA guidelines were used to abstract and assess data. Primary outcomes were associations between HLA-B*1301 and dapsone-induced cADRs in dapsone-tolerant controls. The outcomes are reported as overall OR. Statistical heterogeneity was assessed using the Q statistic and I2 tests. From the 3 included studies, there were 111 unique patients with dapsone-induced cADRs (subsequently used in the meta-analysis), 1165 dapsone-tolerant patients, and 3026 healthy controls. The cases included 64 men and 49 women (2 patients were missing from the meta-analysis; 1 each from 2 of the 3 studies); mean age was 39.7 years. An association between HLA-B*1301 and dapsone-induced cADRs was identified (summary OR, 43.0; 95% CI, 24.0-77.2). Subgroup analyses among types of cADRs produced similar findings in DHS (OR, 51.7; 95% CI, 16.9-158.5), dapsone-induced severe cADRs (Stevens-Johnson syndrome and toxic epidermal necrolysis [SJS/TEN] plus drug rash [adverse skin reaction to a drug] along with eosinophilia and systemic symptoms [DRESS]) (OR, 54.0; 95% Cl, 8.0-366.2), dapsone-induced SJS/TEN (OR, 40.5; 95% CI, 2.8-591.0), and dapsone-induced DRESS (OR, 60.8; 95% CI, 7.4-496.2). There was no heterogeneity (I2 = 0%, P = .38). Associations between HLA-B*1301 and dapsone-induced cADRs were found in dapsone-tolerant and healthy control groups. For patient safety, genetic screening for HLA-B*1301 in Asian populations before dapsone therapy is warranted.

PBRIT: gene prioritization by correlating functional and phenotypic annotations through integrative data fusion.

MotivationComputational gene prioritization can aid in disease gene identification. Here, we propose pBRIT (prioritization using Bayesian Ridge regression and Information Theoretic model), a novel adaptive and scalable prioritization tool, integrating Pubmed abstracts, Gene Ontology, Sequence similarities, Mammalian and Human Phenotype Ontology, Pathway, Interactions, Disease Ontology, Gene Association database and Human Genome Epidemiology database, into the prediction model. We explore and address effects of sparsity and inter-feature dependencies within annotation sources, and the impact of bias towards specific annotations.ResultspBRIT models feature dependencies and sparsity by an Information-Theoretic (data driven) approach and applies intermediate integration based data fusion. Following the hypothesis that genes underlying similar diseases will share functional and phenotype characteristics, it incorporates Bayesian Ridge regression to learn a linear mapping between functional and phenotype annotations. Genes are prioritized on phenotypic concordance to the training genes. We evaluated pBRIT against nine existing methods, and on over 2000 HPO-gene associations retrieved after construction of pBRIT data sources. We achieve maximum AUC scores ranging from 0.92 to 0.96 against benchmark datasets and of 0.80 against the time-stamped HPO entries, indicating good performance with high sensitivity and specificity. Our model shows stable performance with regard to changes in the underlying annotation data, is fast and scalable for implementation in routine pipelines.Availability and implementation http://biomina.be/apps/pbrit/; https://bitbucket.org/medgenua/pbrit.Supplementary information Supplementary data are available at Bioinformatics online.

Association Between HLA genotypes and Oxcarbazepine-induced Cutaneous Adverse Drug Reactions: A Systematic Review and Meta-Analysis.

To systematically review and quantitatively synthesize associations between HLA genotypes and oxcarbazepine-induced cutaneous adverse drug reactions (OXC-cADRs), including Stevens-Johnson syndrome (SJS) and maculopapular rash. Studies investigating associations between HLA genotypes and OXC-cADRs were systematically searched irrespective of language, in PubMed, HuGENet (Human Genome Epidemiology Network), and the Cochrane Library from their inception until January, 2017. Inclusion criteria were studies investigating associations between HLA genotypes and OXC-cADRs that reported sufficient data for calculating the frequency of HLA genotype carriers among cases and controls. Overall odds ratios (ORs) with corresponding 95%CIs were calculated using a random-effects model to determine the association between HLA genotypes and OXC-cADRs. RESULTS: The initial searches identified 91 articles, of which 6 studies met the selection criteria. The studies included 229 patients with OXC-cADRs, 251 OXC-tolerant patients, and 2,358 participants from general populations of Han Chinese, Korean, and Thai ethnicities. Associations between HLA-B*1502 and OXC-induced SJS were found in both the general population [OR=30.2 (95%CI=3.45-264)] and in OXC-tolerant individuals [OR=26.4 (95%CI=7.98-87.6)]. An association between the HLA-B*1502 and OXC-induced maculopapular rash was found in the general population [OR=5.67 (95%CI=2.03-15.9)] while HLA-A*3101 also associated with OXC-induced maculopapular rash [overall OR=29.2 (95%CI=6.70-128)]. CONCLUSIONS: Strong associations between the HLA-B*1502 and OXC-cADRs (SJS and maculopapular rash) were found in both controls from general population and OXC-tolerant groups. There was also an association between HLA-B*3101 and OXC-induced maculopapular rash. For patient safety, genetic screening especially for HLA-B*1502 prior to OXC therapy at least in these closely related ethnicities is warranted. Further studies need to better define other ethnicities at risk and a wider range of MHC gene subtypes.This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

Association between heme oxygenase-1 gene promoter polymorphisms and cancer susceptibility: A meta-analysis.

Numerous studies have focused on the association between heme oxygenase-1 (HO-1) gene promoter polymorphisms and susceptibility to cancer; however, results remain ambiguous. The present systematic Human Genome Epidemiology review and meta-analysis aimed to clarify this association. A systematic search was used to assess the association of HO-1 gene polymorphisms with cancer susceptibility in the PubMed, Web of Science, Cochrane Library, Wanfang Data and China National Knowledge Infrastructure databases, with all reviewed studies published before April 10, 2017. Review Manager 5.3 and Stata 12.0 software were used to perform the meta-analysis. A total of 14 studies were included in the analysis. Overall, no significant associations of the HO-1 (GT)n and T(−413)A polymorphisms with cancer susceptibility were identified. However, subgroup analyses by ethnicity and cancer type indicated that the LL and L-allele (LL+LS) genotypes of HO-1 (GT)n were associated with increased susceptibility to cancer compared with the SS+SL and SS genotypes in the following subgroups: East Asian [LL+LS vs. SS: odds ratio (OR)=1.51, 95% confidence interval (CI)=1.11–2.05, P=0.0003; LL vs. SS+SL: OR=1.44, 95% CI=1.04–2.01, P=0.03; LL vs. SS: OR=1.64, 95% CI=1.07–2.52, P=0.02]; squamous cell carcinoma (LL+LS vs. SS: OR=1.78, 95% CI=1.35–2.34, P<0.05; LL vs. SS+SL: OR=1.71, 95% CI=1.34–2.18, P<0.05; LL vs. SS: OR=2.26, 95% CI =1.62–3.14, P<0.05); and digestive tract cancer + East Asian (LL+LS vs. SS: OR=1.56, 95% CI=1.22–1.98, P<0.05; LL vs. SS: OR=1.80, 95% CI=1.06–3.05, P<0.05). These findings indicated that there was no association of the HO-1 (GT)n and T(−413)A polymorphisms with cancer susceptibility, while the L-allele genotypes (LL and LS) of HO-1 (GT)n may be susceptibility factors for cancer in East Asian, digestive tract cancer in East Asian and squamous cell carcinoma populations. Due to limitations of the reviewed studies, additional large-scale and refined studies are now required to confirm the present findings.

Development and application of Human Genome Epidemiology

Epidemiology is a science that studies distribution of diseases and health in population and its influencing factors, it also studies how to prevent and cure disease and promote health strategies and measures. Epidemiology has developed rapidly in recent years and it is an intercross subject with various other disciplines to form a series of branch disciplines such as Genetic epidemiology, molecular epidemiology, drug epidemiology and tumor epidemiology. With the implementation and completion of Human Genome Project (HGP), Human Genome Epidemiology (HuGE) has emerged at this historic moment. In this review, the development of Human Genome Epidemiology, research content, the construction and structure of relevant network, research standards, as well as the existing results and problems are briefly outlined.

Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct

Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date.Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study.Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution.Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n–3 (ω-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7–like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction < 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates.Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.