Structure‐function relations for old yellow enzyme

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154277/1/fsb2009015004.pd

A programme for risk assessment and minimisation of progressive multifocal leukoencephalopathy developed for vedolizumab clinical trials

Introduction Over the past decade, the potential for drug-associated progressive multifocal leukoencephalopathy (PML) has become an increasingly important consideration in certain drug development programmes, particularly those of immunomodulatory biologics. Whether the risk of PML with an investigational agent is proven (e.g. extrapolated from relevant experience, such as a class effect) or merely theoretical, the serious consequences of acquiring PML require careful risk minimisation and assessment. No single standard for such risk minimisation exists. Vedolizumab is a recently developed monoclonal antibody to α4β7 integrin. Its clinical development necessitated a dedicated PML risk minimisation assessment as part of a global preapproval regulatory requirement. Objective The aim of this study was to describe the multiple risk minimisation elements that were incorporated in vedolizumab clinical trials in inflammatory bowel disease patients as part of the risk assessment and minimisation of PML programme for vedolizumab. Methods A case evaluation algorithm was developed for sequential screening and diagnostic evaluation of subjects who met criteria that indicated a clinical suspicion of PML. An Independent Adjudication Committee provided an independent, unbiased opinion regarding the likelihood of PML. Results Although no cases were detected, all suspected PML events were thoroughly reviewed and successfully adjudicated, making it unlikely that cases were missed. Conclusion We suggest that this programme could serve as a model for pragmatic screening for PML during the clinical development of new drugs

Parentage of Hydatidiform Moles

We were presented with the STR (short tandem repeat) profiles from two separate paternity trios. Each trio consisted of a mother, an alleged father, and products of conception (POC) that contained a hydatidiform mole but no visible fetus. In both cases, antecedent pregnancies had followed alleged sexual assaults. Mole classification and pathogenesis are described in order to explain the analyses and statistical reasoning used in each case. One mole exhibited several loci with two different paternal alleles, indicating it was a dispermic (heterozygous) mole. Maternal decidua contaminated the POC, preventing the identification of paternal obligate alleles (POAs) at some loci. The other mole exhibited only one paternal allele/locus at all loci and no maternal alleles, indicating it was a diandric and diploid (homozygous) mole. In each case, traditional calculations were used to determine paternity indices (PIs) at loci that exhibited one paternal allele/locus. PIs at mole loci with two different paternal alleles/locus were calculated from formulas first used for child chimeras that are always dispermic. Combined paternity indices in both mole cases strongly supported the paternity of each suspect.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155886/1/jfo14291.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155886/2/jfo14291_am.pd

A New Rhesus Macaque Assembly and Annotation for Next-Generation Sequencing Analyses

BACKGROUND: The rhesus macaque (Macaca mulatta) is a key species for advancing biomedical research. Like all draft mammalian genomes, the draft rhesus assembly (rheMac2) has gaps, sequencing errors and misassemblies that have prevented automated annotation pipelines from functioning correctly. Another rhesus macaque assembly, CR_1.0, is also available but is substantially more fragmented than rheMac2 with smaller contigs and scaffolds. Annotations for these two assemblies are limited in completeness and accuracy. High quality assembly and annotation files are required for a wide range of studies including expression, genetic and evolutionary analyses. RESULTS: We report a new de novo assembly of the rhesus macaque genome (MacaM) that incorporates both the original Sanger sequences used to assemble rheMac2 and new Illumina sequences from the same animal. MacaM has a weighted average (N50) contig size of 64 kilobases, more than twice the size of the rheMac2 assembly and almost five times the size of the CR_1.0 assembly. The MacaM chromosome assembly incorporates information from previously unutilized mapping data and preliminary annotation of scaffolds. Independent assessment of the assemblies using Ion Torrent read alignments indicates that MacaM is more complete and accurate than rheMac2 and CR_1.0. We assembled messenger RNA sequences from several rhesus tissues into transcripts which allowed us to identify a total of 11,712 complete proteins representing 9,524 distinct genes. Using a combination of our assembled rhesus macaque transcripts and human transcripts, we annotated 18,757 transcripts and 16,050 genes with complete coding sequences in the MacaM assembly. Further, we demonstrate that the new annotations provide greatly improved accuracy as compared to the current annotations of rheMac2. Finally, we show that the MacaM genome provides an accurate resource for alignment of reads produced by RNA sequence expression studies. CONCLUSIONS: The MacaM assembly and annotation files provide a substantially more complete and accurate representation of the rhesus macaque genome than rheMac2 or CR_1.0 and will serve as an important resource for investigators conducting next-generation sequencing studies with nonhuman primates. REVIEWERS: This article was reviewed by Dr. Lutz Walter, Dr. Soojin Yi and Dr. Kateryna Makova

Breast cancer derived GM-CSF regulates arginase 1 in myeloid cells to promote an immunosuppressive microenvironment

Tumor-infiltrating myeloid cells contribute to the development of the immunosuppressive tumor microenvironment. Myeloid cell expression of arginase 1 (Arg-1) promotes a protumor phenotype by inhibiting T cell function and depleting extracellular L-arginine, but the mechanism underlying this expression, especially in breast cancer, is poorly understood. In breast cancer clinical samples and in our mouse models, we identified tumor derived GM-CSF as the primary regulator of myeloid cell Arg-1 expression and local immune suppression through a gene knockout screen of breast tumor cell-produced factors. The induction of myeloid cell Arg-1 required GM-CSF and a low pH environment. GM-CSF signaling through STAT3, p38 MAPK, and acid signaling through cAMP were required to activate myeloid cell Arg-1 expression in a STAT6 independent manner. Importantly, breast tumor cell-derived GM-CSF promoted tumor progression by inhibiting host anti-tumor immunity, driving a significant accumulation of Arg-1 expressing myeloid cells compared to lung and melanoma tumors with minimal GM-CSF expression. Blockade of tumoral GM-CSF enhanced the efficacy of tumor-specific adoptive T-cell therapy and immune checkpoint blockade. Taken together, breast tumor cell-derived GM-CSF contributes to the development of the immunosuppressive breast cancer microenvironment by regulating myeloid cell Arg-1 expression and can be targeted to enhance breast cancer immunotherapy

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.