Sequencing-based fine-mapping and in silico functional characterization of the 10q24.32 arsenic metabolism efficiency locus across multiple arsenic-exposed populations.

Inorganic arsenic is highly toxic and carcinogenic to humans. Exposed individuals vary in their ability to metabolize arsenic, and variability in arsenic metabolism efficiency (AME) is associated with risks of arsenic-related toxicities. Inherited genetic variation in the 10q24.32 region, near the arsenic methyltransferase (AS3MT) gene, is associated with urine-based measures of AME in multiple arsenic-exposed populations. To identify potential causal variants in this region, we applied fine mapping approaches to targeted sequencing data generated for exposed individuals from Bangladeshi, American Indian, and European American populations (n = 2,357, 557, and 648 respectively). We identified three independent association signals for Bangladeshis, two for American Indians, and one for European Americans. The size of the confidence sets for each signal varied from 4 to 85 variants. There was one signal shared across all three populations, represented by the same SNP in American Indians and European Americans (rs191177668) and in strong linkage disequilibrium (LD) with a lead SNP in Bangladesh (rs145537350). Beyond this shared signal, differences in LD patterns, minor allele frequency (MAF) (e.g., rs12573221 ~13% in Bangladesh ~0.2% among American Indians), and/or heterogeneity in effect sizes across populations likely contributed to the apparent population specificity of the additional identified signals. One of our potential causal variants influences AS3MT expression and nearby DNA methylation in numerous GTEx tissue types (with rs4919690 as a likely causal variant). Several SNPs in our confidence sets overlap transcription factor binding sites and cis-regulatory elements (from ENCODE). Taken together, our analyses reveal multiple potential causal variants in the 10q24.32 region influencing AME, including a variant shared across populations, and elucidate potential biological mechanisms underlying the impact of genetic variation on AME.

Rare, Protein-Altering Variants in AS3MT and Arsenic Metabolism Efficiency: A Multi-Population Association Study.

BACKGROUND: Common genetic variation in the arsenic methyltransferase (AS3MT) gene region is known to be associated with arsenic metabolism efficiency (AME), measured as the percentage of dimethylarsinic acid (DMA%) in the urine. Rare, protein-altering variants in AS3MT could have even larger effects on AME, but their contribution to AME has not been investigated. OBJECTIVES: We estimated the impact of rare, protein-coding variation in AS3MT on AME using a multi-population approach to facilitate the discovery of population-specific and shared causal rare variants. METHODS: We generated targeted DNA sequencing data for the coding regions of AS3MT for three arsenic-exposed cohorts with existing data on arsenic species measured in urine: Health Effects of Arsenic Longitudinal Study (HEALS, n=2,434), Strong Heart Study (SHS, n=868), and New Hampshire Skin Cancer Study (NHSCS, n=666). We assessed the collective effects of rare (allele frequency <1%), protein-altering AS3MT variants on DMA%, using multiple approaches, including a test of the association between rare allele carrier status (yes/no) and DMA% using linear regression (adjusted for common variants in 10q24.32 region, age, sex, and population structure). RESULTS: We identified 23 carriers of rare-protein-altering AS3MT variant across all cohorts (13 in HEALS and 5 in both SHS and NHSCS), including 6 carriers of predicted loss-of-function variants. DMA% was 6-10% lower in carriers compared with noncarriers in HEALS [ß=-9.4 (95% CI: -13.9, -4.8)], SHS [ß=-6.9 (95% CI: -13.6, -0.2)], and NHSCS [ß=-8.7 (95% CI: -15.6, -2.2)]. In meta-analyses across cohorts, DMA% was 8.7% lower in carriers [ß=-8.7 (95% CI: -11.9, -5.4)]. DISCUSSION: Rare, protein-altering variants in AS3MT were associated with lower mean DMA%, an indicator of reduced AME. Although a small percentage of the population (0.5-0.7%) carry these variants, they are associated with a 6-10% decrease in DMA% that is consistent across multiple ancestral and environmental backgrounds. https://doi.org/10.1289/EHP8152.

Engineering brown fat into skeletal muscle using ultrasound-targeted microbubble destruction gene delivery in obese Zucker rats: Proof of concept design.

Ultrasound-targeted microbubble destruction (UTMD) is a novel means of tissue-specific gene delivery. This approach systemically infuses transgenes precoupled to gas-filled lipid microbubbles that are burst within the microvasculature of target tissues via an ultrasound signal resulting in release of DNA and transfection of neighboring cells within the tissue. Previous work has shown that adenovirus containing cDNA of UCP-1, injected into the epididymal fat pads in mice, induced localized fat depletion, improving glucose tolerance, and decreasing food intake in obese diabetic mice. Our group recently demonstrated that gene therapy by UTMD achieved beta cell regeneration in streptozotocin (STZ)-treated mice and baboons. We hypothesized that gene therapy with BMP7/PRDM16/PPARGC1A in skeletal muscle (SKM) of obese Zucker diabetic fatty (fa/fa) rats using UTMD technology would produce a brown adipose tissue (BAT) phenotype with UCP-1 overexpression. This study was designed as a proof of concept (POC) project. Obese Zucker rats were administered plasmid cDNA contructs encoding a gene cocktail with BMP7/PRDM16/PPARGC1A incorporated within microbubbles and intravenously delivered into their left thigh. Controls received UTMD with plasmids driving a DsRed reporter gene. An ultrasound transducer was directed to the thigh to disrupt the microbubbles within the microcirculation. Blood samples were drawn at baseline, and after treatment to measure glucose, insulin, and free fatty acids levels. SKM was harvested for immunohistochemistry (IHC). Our IHC results showed a reliable pattern of effective UTMD-based gene delivery in enhancing SKM overexpression of the UCP-1 gene. This clearly indicates that our plasmid DNA construct encoding the gene combination of PRDM16, PPARGC1A, and BMP7 reprogrammed adult SKM tissue into brown adipose cells in vivo. Our pilot established POC showing that the administration of the gene cocktail to SKM in this rat model of genetic obesity using UTMD gene therapy, engineered a BAT phenotype with UCP-1 over-expression. © 2017 IUBMB Life, 69(9):745-755, 2017.

Association of TMTC2 With Human Nonsyndromic Sensorineural Hearing Loss.

IMPORTANCE: Sensorineural hearing loss (SNHL) is commonly caused by conditions that affect cochlear structures or the auditory nerve, and the genes identified as causing SNHL to date only explain a fraction of the overall genetic risk for this debilitating disorder. It is likely that other genes and mutations also cause SNHL. OBJECTIVE: To identify a candidate gene that causes bilateral, symmetric, progressive SNHL in a large multigeneration family of Northern European descent. DESIGN, SETTING, AND PARTICIPANTS: In this prospective genotype and phenotype study performed from January 1, 2006, through April 1, 2016, a 6-generation family of Northern European descent with 19 individuals having reported early-onset hearing loss suggestive of an autosomal dominant inheritance were studied at a tertiary academic medical center. In addition, 179 unrelated adult individuals with SNHL and 186 adult individuals reporting nondeafness were examined. MAIN OUTCOMES AND MEASURES: Sensorineural hearing loss. RESULTS: Nine family members (5 women [55.6%]) provided clinical audiometric and medical records that documented hearing loss. The hearing loss is characterized as bilateral, symmetric, progressive SNHL that reached severe to profound loss in childhood. Audiometric configurations demonstrated a characteristic dip at 1000 to 2000 Hz. All affected family members wear hearing aids or have undergone cochlear implantation. Exome sequencing and linkage and association analyses identified a fully penetrant sequence variant (rs35725509) on chromosome 12q21 (logarithm of odds, 3.3) in the TMTC2 gene region that segregates with SNHL in this family. This gene explains the SNHL occurrence in this family. The variant is also associated with SNHL in a cohort of 363 unrelated individuals (179 patients with confirmed SNHL and 184 controls, P = 7 × 10-4). CONCLUSIONS AND RELEVANCE: A previously uncharacterized gene, TMTC2, has been identified as a candidate for causing progressive SNHL in humans. This finding identifies a novel locus that causes autosomal dominant SNHL and therefore a more detailed understanding of the genetic basis of SNHL. Because TMTC2 has not been previously reported to regulate auditory function, the discovery reveals a potentially new, uncharacterized mechanism of hearing loss.

An epigenetic map of age-associated autosomal loci in northern European families at high risk for the metabolic syndrome.

BACKGROUND: The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6-85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese. RESULTS: We found 22,122 genome-wide significant age-associated CpG sites (P α=0.05 = 3.65 × 10(-7) after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic 'hot-spots' of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (n = 241) and negatively (n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 × 10(-3)) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 × 10(-3)) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 × 10(-7)) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without. CONCLUSION: We conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS.

A comprehensive analysis of adiponectin QTLs using SNP association, SNP cis-effects on peripheral blood gene expression and gene expression correlation identified novel metabolic syndrome (MetS) genes with potential role in carcinogenesis and systemic inflammation.

BACKGROUND: Metabolic syndrome (MetS) is an aberration associated with increased risk for cancer and inflammation. Adiponectin, an adipocyte-produced abundant protein hormone, has countering effect on the diabetogenic and atherogenic components of MetS. Plasma levels of adiponectin are negatively correlated with onset of cancer and cancer patient mortality. We previously performed microsatellite linkage analyses using adiponectin as a surrogate marker and revealed two QTLs on chr5 (5p14) and chr14 (14q13). METHODS: Using individuals from 85 extended families that contributed to the linkage and who were measured for 42 clinical and biologic MetS phenotypes, we tested QTL-based SNP associations, peripheral white blood cell (PWBC) gene expression, and the effects of cis-acting SNPs on gene expression to discover genomic elements that could affect the pathophysiology and complications of MetS. RESULTS: Adiponectin levels were found to be highly intercorrelated phenotypically with the majority of MetS traits. QTL-specific haplotype-tagging SNPs associated with MetS phenotypes were annotated to 14 genes whose function could influence MetS biology as well as oncogenesis or inflammation. These were mechanistically categorized into four groups: cell-cell adhesion and mobility, signal transduction, transcription and protein sorting. Four genes were highly prioritized: cadherin 18 (CDH18), myosin X (MYO10), anchor protein 6 of AMPK (AKAP6), and neuronal PAS domain protein 3 (NPAS3). PWBC expression was detectable only for the following genes with multi-organ or with multi-function properties: NPAS3, MARCH6, MYO10 and FBXL7. Strong evidence of cis-effects on the expression of MYO10 in PWBC was found with SNPs clustered near the gene's transcription start site. MYO10 expression in PWBC was marginally correlated with body composition (p = 0.065) and adipokine levels in the periphery (p = 0.064). Variants of genes AKAP6, NPAS3, MARCH6 and FBXL7 have been previously reported to be associated with insulin resistance, inflammatory markers or adiposity studies using genome-wide approaches whereas associations of CDH18 and MYO10 with MetS traits have not been reported before. CONCLUSIONS: Adiponectin QTLs-based SNP association and mRNA expression identified genes that could mediate the association between MetS and cancer or inflammation.

A genome-wide integrative genomic study localizes genetic factors influencing antibodies against Epstein-Barr virus nuclear antigen 1 (EBNA-1).

Infection with Epstein-Barr virus (EBV) is highly prevalent worldwide, and it has been associated with infectious mononucleosis and severe diseases including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal lymphoma, and lymphoproliferative disorders. Although EBV has been the focus of extensive research, much still remains unknown concerning what makes some individuals more sensitive to infection and to adverse outcomes as a result of infection. Here we use an integrative genomics approach in order to localize genetic factors influencing levels of Epstein Barr virus (EBV) nuclear antigen-1 (EBNA-1) IgG antibodies, as a measure of history of infection with this pathogen, in large Mexican American families. Genome-wide evidence of both significant linkage and association was obtained on chromosome 6 in the human leukocyte antigen (HLA) region and replicated in an independent Mexican American sample of large families (minimum p-value in combined analysis of both datasets is 1.4×10(-15) for SNPs rs477515 and rs2516049). Conditional association analyses indicate the presence of at least two separate loci within MHC class II, and along with lymphocyte expression data suggest genes HLA-DRB1 and HLA-DQB1 as the best candidates. The association signals are specific to EBV and are not found with IgG antibodies to 12 other pathogens examined, and therefore do not simply reveal a general HLA effect. We investigated whether SNPs significantly associated with diseases in which EBV is known or suspected to play a role (namely nasopharyngeal lymphoma, Hodgkin lymphoma, systemic lupus erythematosus, and multiple sclerosis) also show evidence of associated with EBNA-1 antibody levels, finding an overlap only for the HLA locus, but none elsewhere in the genome. The significance of this work is that a major locus related to EBV infection has been identified, which may ultimately reveal the underlying mechanisms by which the immune system regulates infection with this pathogen.

Genotype×age interaction in human transcriptional ageing.

Individual differences in biological ageing (i.e., the rate of physiological response to the passage of time) may be due in part to genotype-specific variation in gene action. However, the sources of heritable variation in human age-related gene expression profiles are largely unknown. We have profiled genome-wide expression in peripheral blood mononuclear cells from 1240 individuals in large families and found 4472 human autosomal transcripts, representing ~4349 genes, significantly correlated with age. We identified 623 transcripts that show genotype by age interaction in addition to a main effect of age, defining a large set of novel candidates for characterization of the mechanisms of differential biological ageing. We applied a novel SNP genotype × age interaction test to one of these candidates, the ubiquilin-like gene UBQLNL, and found evidence of joint cis-association and genotype by age interaction as well as trans-genotype by age interaction for UBQLNL expression. Both UBQLNL expression levels at recruitment and cis genotype are associated with longitudinal cancer risk in our study cohort.

Genome-wide association scan identifies a risk locus for preeclampsia on 2q14, near the inhibin, beta B gene.

Elucidating the genetic architecture of preeclampsia is a major goal in obstetric medicine. We have performed a genome-wide association study (GWAS) for preeclampsia in unrelated Australian individuals of Caucasian ancestry using the Illumina OmniExpress-12 BeadChip to successfully genotype 648,175 SNPs in 538 preeclampsia cases and 540 normal pregnancy controls. Two SNP associations (rs7579169, p = 3.58×10(-7), OR = 1.57; rs12711941, p = 4.26×10(-7), OR = 1.56) satisfied our genome-wide significance threshold (modified Bonferroni p<5.11×10(-7)). These SNPs reside in an intergenic region less than 15 kb downstream from the 3' terminus of the Inhibin, beta B (INHBB) gene on 2q14.2. They are in linkage disequilibrium (LD) with each other (r(2) = 0.92), but not (r(2)<0.80) with any other genotyped SNP ±250 kb. DNA re-sequencing in and around the INHBB structural gene identified an additional 25 variants. Of the 21 variants that we successfully genotyped back in the case-control cohort the most significant association observed was for a third intergenic SNP (rs7576192, p = 1.48×10(-7), OR = 1.59) in strong LD with the two significant GWAS SNPs (r(2)>0.92). We attempted to provide evidence of a putative regulatory role for these SNPs using bioinformatic analyses and found that they all reside within regions of low sequence conservation and/or low complexity, suggesting functional importance is low. We also explored the mRNA expression in decidua of genes ±500 kb of INHBB and found a nominally significant correlation between a transcript encoded by the EPB41L5 gene, ∼250 kb centromeric to INHBB, and preeclampsia (p = 0.03). We were unable to replicate the associations shown by the significant GWAS SNPs in case-control cohorts from Norway and Finland, leading us to conclude that it is more likely that these SNPs are in LD with as yet unidentified causal variant(s).

Genome-wide association and linkage identify modifier loci of lung disease severity in cystic fibrosis at 11p13 and 20q13.2.

A combined genome-wide association and linkage study was used to identify loci causing variation in cystic fibrosis lung disease severity. We identified a significant association (P = 3.34 × 10(-8)) near EHF and APIP (chr11p13) in p.Phe508del homozygotes (n = 1,978). The association replicated in p.Phe508del homozygotes (P = 0.006) from a separate family based study (n = 557), with P = 1.49 × 10(-9) for the three-study joint meta-analysis. Linkage analysis of 486 sibling pairs from the family based study identified a significant quantitative trait locus on chromosome 20q13.2 (log(10) odds = 5.03). Our findings provide insight into the causes of variation in lung disease severity in cystic fibrosis and suggest new therapeutic targets for this life-limiting disorder.

Genetic Analysis Workshop 17 mini-exome simulation.

The data set simulated for Genetic Analysis Workshop 17 was designed to mimic a subset of data that might be produced in a full exome screen for a complex disorder and related risk factors in order to permit workshop participants to investigate issues of study design and statistical genetic analysis. Real sequence data from the 1000 Genomes Project formed the basis for simulating a common disease trait with a prevalence of 30% and three related quantitative risk factors in a sample of 697 unrelated individuals and a second sample of 697 individuals in large, extended pedigrees. Called genotypes for 24,487 autosomal markers assigned to 3,205 genes and simulated affection status, quantitative traits, age, sex, pedigree relationships, and cigarette smoking were provided to workshop participants. The simulating model included both common and rare variants with minor allele frequencies ranging from 0.07% to 25.8% and a wide range of effect sizes for these variants. Genotype-smoking interaction effects were included for variants in one gene. Functional variants were concentrated in genes selected from specific biological pathways and were selected on the basis of the predicted deleteriousness of the coding change. For each sample, unrelated individuals and family, 200 replicates of the phenotypes were simulated.

Transcriptomic epidemiology of smoking: the effect of smoking on gene expression in lymphocytes.

BACKGROUND: This investigation offers insights into system-wide pathological processes induced in response to cigarette smoke exposure by determining its influences at the gene expression level. METHODS: We obtained genome-wide quantitative transcriptional profiles from 1,240 individuals from the San Antonio Family Heart Study, including 297 current smokers. Using lymphocyte samples, we identified 20,413 transcripts with significantly detectable expression levels, including both known and predicted genes. Correlation between smoking and gene expression levels was determined using a regression model that allows for residual genetic effects. RESULTS: With a conservative false-discovery rate of 5% we identified 323 unique genes (342 transcripts) whose expression levels were significantly correlated with smoking behavior. These genes showed significant over-representation within a range of functional categories that correspond well with known smoking-related pathologies, including immune response, cell death, cancer, natural killer cell signaling and xenobiotic metabolism. CONCLUSIONS: Our results indicate that not only individual genes but entire networks of gene interaction are influenced by cigarette smoking. This is the largest in vivo transcriptomic epidemiological study of smoking to date and reveals the significant and comprehensive influence of cigarette smoke, as an environmental variable, on the expression of genes. The central importance of this manuscript is to provide a summary of the relationships between gene expression and smoking in this exceptionally large cross-sectional data set.

[Transciptome among Mexicans: a large scale methodology to analyze the genetics expression profile of simultaneous samples in muscle, adipose tissue and lymphocytes obtained from the same individual]. / Transcriptoma en mexicanos: metodología para analizar el perfil de expresión genética de gran escala en muestras simultáneas de tejido muscular, adiposo y linfocitos obtenidas en un mismo individuo.

OBJECTIVE: We describe the methodology used to analyze multiple transcripts using microarray techniques in simultaneous biopsies of muscle, adipose tissue and lymphocytes obtained from the same individual as part of the standard protocol of the Genetics of Metabolic Diseases in Mexico: GEMM Family Study. METHODS: We recruited 4 healthy male subjects with BM1 20-41, who signed an informed consent letter. Subjects participated in a clinical examination that included anthropometric and body composition measurements, muscle biopsies (vastus lateralis) subcutaneous fat biopsies anda blood draw. All samples provided sufficient amplified RNA for microarray analysis. Total RNA was extracted from the biopsy samples and amplified for analysis. RESULTS: Of the 48,687 transcript targets queried, 39.4% were detectable in a least one of the studied tissues. Leptin was not detectable in lymphocytes, weakly expressed in muscle, but overexpressed and highly correlated with BMI in subcutaneous fat. Another example was GLUT4, which was detectable only in muscle and not correlated with BMI. Expression level concordance was 0.7 (p< 0.001) for the three tissues studied. CONCLUSIONS: We demonstrated the feasibility of carrying out simultaneous analysis of gene expression in multiple tissues, concordance of genetic expression in different tissues, and obtained confidence that this method corroborates the expected biological relationships among LEPand GLUT4. TheGEMM study will provide a broad and valuable overview on metabolic diseases, including obesity and type 2 diabetes.