Analysis of Beta-Cell Gene Expression Reveals Inflammatory Signaling and Evidence of Dedifferentiation following Human Islet Isolation and Culture

The stresses encountered during islet isolation and culture may have deleterious effects on beta-cell physiology. However, the biological response of human islet cells to isolation remains poorly characterized. A better understanding of the network of signaling pathways induced by islet isolation and culturing may lead to strategies aimed at improving islet graft survival and function. Laser capture microdissection (LCM) was used to extract beta-cell RNA from 1) intact pancreatic islets, 2) freshly isolated islets, 3) islets cultured for 3 days, and changes in gene expression were examined by microarray analysis. We identified a strong inflammatory response induced by islet isolation that continues during in-vitro culture manifested by upregulation of several cytokines and cytokine-receptors. The most highly upregulated gene, interleukin-8 (IL-8), was induced by 3.6-fold following islet isolation and 56-fold after 3 days in culture. Immunofluorescence studies showed that the majority of IL-8 was produced by beta-cells themselves. We also observed that several pancreas-specific transcription factors were down-regulated in cultured islets. Concordantly, several pancreatic progenitor cell-specific transcription factors like SOX4, SOX9, and ID2 were upregulated in cultured islets, suggesting progressive transformation of mature beta-cell phenotype toward an immature endocrine cell phenotype. Our findings suggest islet isolation and culture induces an inflammatory response and loss of the mature endocrine cell phenotype. A better understanding of the signals required to maintain a mature beta-cell phenotype may help improve the efficacy of islet transplantation

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Analysis of KLF transcription factor family gene variants in type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>The Krüppel-like factor (<it>KLF</it>) family consists of transcription factors that can activate or repress different genes implicated in processes such as differentiation, development, and cell cycle progression. Moreover, several of these proteins have been implicated in glucose homeostasis, making them candidate genes for involvement in type 2 diabetes (T2D).</p> <p>Methods</p> <p>Variants of nine <it>KLF </it>genes were genotyped in T2D cases and controls and analysed in a two-stage study. The first case-control set included 365 T2D patients with a strong family history of T2D and 363 normoglycemic individuals and the second set, 750 T2D patients and 741 normoglycemic individuals, all of French origin. The SNPs of six <it>KLF </it>genes were genotyped by Taqman^®SNP Genotyping Assays. The other three <it>KLF </it>genes (KLF2, -15 and -16) were screened and the identified frequent variants of these genes were analysed in the case-control studies.</p> <p>Results</p> <p>Three of the 28 SNPs showed a trend to be associated with T2D in our first case-control set (P < 0.10). These SNPs, located in the <it>KLF2, KLF4 </it>and <it>KLF5 </it>gene were then analysed in our second replication set, but analysis of this set and the combined analysis of the three variants in all 2,219 individuals did not show an association with T2D in this French population. As the <it>KLF2</it>, -15 and -16 variants were representative for the genetic variability in these genes, we conclude they do not contribute to genetic susceptibility for T2D.</p> <p>Conclusion</p> <p>It is unlikely that variants in different members of the <it>KLF </it>gene family play a major role in T2D in the French population.</p

A genome-wide association study of anorexia nervosa

Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2,907 cases with AN from 14 countries (15 sites) and 14,860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery datasets. Seventy-six (72 independent) SNPs were taken forward for in silico (two datasets) or de novo (13 datasets) replication genotyping in 2,677 independent AN cases and 8,629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication datasets comprised 5,551 AN cases and 21,080 controls. AN subtype analyses (1,606 AN restricting; 1,445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01×10−7) in SOX2OT and rs17030795 (P=5.84×10−6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76×10−6) between CUL3 and FAM124B and rs1886797 (P=8.05×10−6) near SPATA13. Comparing discovery to replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P= 4×10−6), strongly suggesting that true findings exist but that our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field

Heterogeneous effects of genetic variants and traits associated with fasting insulin on cardiometabolic outcomes.

Elevated fasting insulin levels (FI), indicative of altered insulin secretion and sensitivity, may precede type 2 diabetes (T2D) and cardiovascular disease onset. In this study, we group FI-associated genetic variants based on their genetic and phenotypic similarities and identify seven clusters with distinct mechanisms contributing to elevated FI levels. Clusters fall into two types: non-diabetogenic hyperinsulinemia, where clusters are not associated with increased T2D risk, and diabetogenic hyperinsulinemia, where T2D associations are driven by body fat distribution, liver function, circulating lipids, or inflammation. In over 1.1 million multi-ancestry individuals, we demonstrated that diabetogenic hyperinsulinemia cluster-specific polygenic scores exhibit varying risks for cardiovascular conditions, including coronary artery disease, myocardial infarction (MI), and stroke. Notably, the visceral adiposity cluster shows sex-specific effects for MI risk in males without T2D. This study underscores processes that decouple elevated FI levels from T2D and cardiovascular risk, offering new avenues for investigating process-specific pathways of disease

Three-dimensional structure of β-cell-specific zinc transporter, ZnT-8, predicted from the type 2 diabetes-associated gene variant SLC30A8 R325W

<p>Abstract</p> <p>Background</p> <p>We examined the effects of the R325W mutation on the three-dimensional (3D) structure of the β-cell-specific Zn²⁺(zinc) transporter ZnT-8.</p> <p>Methods</p> <p>A model of the C-terminal domain of the human ZnT-8 protein was generated by homology modeling based on the known crystal structure of the <it>Escherichia coli </it>(<it>E. coli</it>) zinc transporter YiiP at 3.8 Å resolution.</p> <p>Results</p> <p>The homodimer ZnT-8 protein structure exists as a Y-shaped architecture with Arg325 located at the ultimate bottom of this motif at approximately 13.5 Å from the transmembrane domain juncture. The C-terminal domain sequences of the human ZnT-8 protein and the <it>E. coli </it>zinc transporter YiiP share 12.3% identical and 39.5% homologous residues resulting in an overall homology of 51.8%. Validation statistics of the homology model showed a reasonable quality of the model. The C-terminal domain exhibited an αββαβ fold with Arg325 as the penultimate N-terminal residue of the α2-helix. The side chains of both Arg325 and Trp325 point away from the interface with the other monomer, whereas the ε-NH₃⁺group of Arg325 is predicted to form an ionic interaction with the β-COO^-group of Asp326 as well as Asp295. An amino acid alignment of the β2-α2 C-terminal loop domain revealed a variety of neutral amino acids at position 325 of different ZnT-8 proteins.</p> <p>Conclusions</p> <p>Our validated homology models predict that both Arg325 and Trp325, amino acids with a helix-forming behavior, and penultimate N-terminal residues in the α2-helix of the C-terminal domain, are shielded by the planar surface of the three cytoplasmic β-strands and hence unable to affect the sensing capacity of the C-terminal domain. Moreover, the amino acid residue at position 325 is too far removed from the docking and transporter parts of ZnT-8 to affect their local protein conformations. These data indicate that the inherited R325W abnormality in SLC30A8 may be tolerated and results in adequate zinc transfer to the correct sites in the pancreatic islet cells and are consistent with the observation that the <it>SLC30A8 </it>gene variant R325W has a low predicted value for future type 2 diabetes at population-based level.</p

The living microarray: a high-throughput platform for measuring transcription dynamics in single cells

<p>Abstract</p> <p>Background</p> <p>Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional regulation and Systems Biology. However, endpoint measurements obtained from methods that pool populations of cells are not amenable to studying time-dependent processes that show cell heterogeneity.</p> <p>Results</p> <p>Here we describe a high-throughput platform for measuring transcriptional changes in real time in single mammalian cells. By using reverse transfection microarrays we are able to transfect fluorescent reporter plasmids into 600 independent clusters of cells plated on a single microscope slide and image these clusters every 20 minutes. We use a fast-maturing, destabilized and nuclear-localized reporter that is suitable for automated segmentation to accurately measure promoter activity in single cells. We tested this platform with synthetic drug-inducible promoters that showed robust induction over 24 hours. Automated segmentation and tracking of over 11 million cell images during this period revealed that cells display substantial heterogeneity in their responses to the applied treatment, including a large proportion of transfected cells that do not respond at all.</p> <p>Conclusions</p> <p>The results from our single-cell analysis suggest that methods that measure average cellular responses, such as DNA microarrays, RT-PCR and chromatin immunoprecipitation, characterize a response skewed by a subset of cells in the population. Our method is scalable and readily adaptable to studying complex systems, including cell proliferation, differentiation and apoptosis.</p

The aldehyde dehydrogenase enzyme 7A1 is functionally involved in prostate cancer bone metastasis

High aldehyde dehydrogenase (ALDH) activity can be used to identify tumor-initiating and metastasis-initiating cells in various human carcinomas, including prostate cancer. To date, the functional importance of ALDH enzymes in prostate carcinogenesis, progression and metastasis has remained elusive. Previously we identified strong expression of ALDH7A1 in human prostate cancer cell lines, primary tumors and matched bone metastases. In this study, we evaluated whether ALDH7A1 is required for the acquisition of a metastatic stem/progenitor cell phenotype in human prostate cancer. Knockdown of ALDH7A1 expression resulted in a decrease of the α2hi/αvhi/CD44+ stem/progenitor cell subpopulation in the human prostate cancer cell line PC-3M-Pro4. In addition, ALDH7A1 knockdown significantly inhibited the clonogenic and migratory ability of human prostate cancer cells in vitro. Furthermore, a number of genes/factors involved in migration, invasion and metastasis were affected including transcription factors (snail, snail2, and twist) and osteopontin, an ECM molecule involved in metastasis. Knockdown of ALDH7A1 resulted in decreased intra-bone growth and inhibited experimentally induced (bone) metastasis, while intra-prostatic growth was not affected. In line with these observations, evidence is presented that TGF-β, a key player in cancer invasiveness and bone metastasis, strongly induced ALDH activity while BMP7 (an antagonist of TGF-β signaling) down-regulated ALDH activity. Our findings show, for the first time, that the ALDH7A1 enzyme is functionally involved in the formation of bone metastases and that the effect appeared dependent on the microenvironment, i.e., bone versus prostate

The genetic discrimination observatory : confronting novel issues in genetic discrimination

Genetic discrimination (GD) is the differential or unfair profiling of an individual on the basis of genetic data. This article summarizes the actions of the Genetic Discrimination Observatory (GDO) in addressing GD and recent developments in GD since late 2020. It shows how GD can take many forms in today’s rapidly evolving society.http://www.journals.elsevier.com/trends-in-geneticshj2022Immunolog