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Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10\(^{−9}\)). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10\(^{−8}\)), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.
This paper provides an overview of current progress in the technological advances and the use of deep brain stimulation (DBS) to treat neurological and neuropsychiatric disorders, as presented by participants of the Fourth Annual DBS Think Tank, which was convened in March 2016 in conjunction with the Center for Movement Disorders and Neurorestoration at the University of Florida, Gainesveille FL, USA. The Think Tank discussions first focused on policy and advocacy in DBS research and clinical practice, formation of registries, and issues involving the use of DBS in the treatment of Tourette Syndrome. Next, advances in the use of neuroimaging and electrochemical markers to enhance DBS specificity were addressed. Updates on ongoing use and developments of DBS for the treatment of Parkinson's disease, essential tremor, Alzheimer's disease, depression, post-traumatic stress disorder, obesity, addiction were presented, and progress toward innovation(s) in closed-loop applications were discussed. Each section of these proceedings provides updates and highlights of new information as presented at this year's international Think Tank, with a view toward current and near future advancement of the field.
Context:
Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2–11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values.
Objective:
Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy.
Design:
Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19–84 yr) and 45 ACC patients (20–80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26–201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids.
Results:
Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers.
Conclusions:
Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.
Delivery of crop pollination services is an insufficient argument for wild pollinator conservation
(2015)
There is compelling evidence that more diverse ecosystems deliver greater benefits to people, and these ecosystem services have become a key argument for biodiversity conservation. However, it is unclear how much biodiversity is needed to deliver ecosystem services in a cost- effective way. Here we show that, while the contribution of wild bees to crop production is significant, service delivery is restricted to a limited subset of all known bee species. Across crops, years and biogeographical regions, crop-visiting wild bee communities are dominated by a small number of common species, and threatened species are rarely observed on crops. Dominant crop pollinators persist under agricultural expansion and many are easily enhanced by simple conservation measures, suggesting that cost- effective management strategies to promote crop pollination should target a different set of species than management strategies to promote threatened bees. Conserving the biological diversity of bees therefore requires more than just ecosystem-service-based arguments.
Mass-flowering crops (MFCs) are increasingly cultivated and might influence pollinator communities in MFC fields and nearby semi-natural habitats (SNHs). Across six European regions and 2 years, we assessed how landscape-scale cover of MFCs affected pollinator densities in 408 MFC fields and adjacent SNHs. In MFC fields, densities of bumblebees, solitary bees, managed honeybees and hoverflies were negatively related to the cover of MFCs in the landscape. In SNHs, densities of bumblebees declined with increasing cover of MFCs but densities of honeybees increased. The densities of all pollinators were generally unrelated to the cover of SNHs in the landscape. Although MFC fields apparently attracted pollinators from SNHs, in landscapes with large areas of MFCs they became diluted. The resulting lower densities might negatively affect yields of pollinator- dependent crops and the reproductive success of wild plants. An expansion of MFCs needs to be accompanied by pollinator-supporting practices in agricultural landscapes.
Deafness, the most frequent sensory deficit in humans, is extremely heterogeneous with hundreds of genes involved. Clinical and genetic analyses of an extended consanguineous family with pre-lingual, moderate-to-profound autosomal recessive sensorineural hearing loss, allowed us to identify CLRN2, encoding a tetraspan protein, as a new deafness gene. Homozygosity mapping followed by exome sequencing identified a 14.96 Mb locus on chromosome 4p15.32p15.1 containing a likely pathogenic missense variant in CLRN2 (c.494C > A, NM_001079827.2) segregating with the disease. Using in vitro RNA splicing analysis, we show that the CLRN2 c.494C > A variant leads to two events: (1) the substitution of a highly conserved threonine (uncharged amino acid) to lysine (charged amino acid) at position 165, p.(Thr165Lys), and (2) aberrant splicing, with the retention of intron 2 resulting in a stop codon after 26 additional amino acids, p.(Gly146Lysfs*26). Expression studies and phenotyping of newly produced zebrafish and mouse models deficient for clarin 2 further confirm that clarin 2, expressed in the inner ear hair cells, is essential for normal organization and maintenance of the auditory hair bundles, and for hearing function. Together, our findings identify CLRN2 as a new deafness gene, which will impact future diagnosis and treatment for deaf patients.
Regulation of Human γδ T Cells by BTN3A1 Protein Stability and ATP-Binding Cassette Transporters
(2018)
Activation of human Vγ9/Vδ2 T cells by “phosphoantigens” (pAg), the microbial metabolite (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (HMB-PP) and the endogenous isoprenoid intermediate isopentenyl pyrophosphate, requires expression of butyrophilin BTN3A molecules by presenting cells. However, the precise mechanism of activation of Vγ9/Vδ2 T cells by BTN3A molecules remains elusive. It is not clear what conformation of the three BTN3A isoforms transmits activation signals nor how externally delivered pAg accesses the cytosolic B30.2 domain of BTN3A1. To approach these problems, we studied two HLA haplo-identical HeLa cell lines, termed HeLa-L and HeLa-M, which showed marked differences in pAg-dependent stimulation of Vγ9/Vδ2 T cells. Levels of IFN-γ secretion by Vγ9/Vδ2 T cells were profoundly increased by pAg loading, or by binding of the pan-BTN3A specific agonist antibody CD277 20.1, in HeLa-M compared to HeLa-L cells. IL-2 production from a murine hybridoma T cell line expressing human Vγ9/Vδ2 T cell receptor (TCR) transgenes confirmed that the differential responsiveness to HeLa-L and HeLa-M was TCR dependent. By tissue typing, both HeLa lines were shown to be genetically identical and full-length transcripts of the three BTN3A isoforms were detected in equal abundance with no sequence variation. Expression of BTN3A and interacting molecules, such as periplakin or RhoB, did not account for the functional variation between HeLa-L and HeLa-M cells. Instead, the data implicate a checkpoint controlling BTN3A1 stability and protein trafficking, acting at an early time point in its maturation. In addition, plasma membrane profiling was used to identify proteins upregulated in HMB-PP-treated HeLa-M. ABCG2, a member of the ATP-binding cassette (ABC) transporter family was the most significant candidate, which crucially showed reduced expression in HeLa-L. Expression of a subset of ABC transporters, including ABCA1 and ABCG1, correlated with efficiency of T cell activation by cytokine secretion, although direct evidence of a functional role was not obtained by knockdown experiments. Our findings indicate a link between members of the ABC protein superfamily and the BTN3A-dependent activation of γδ T cells by endogenous and exogenous pAg.
Background
Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype–phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted.
Results
Two of these rules—one associated with eating disorder and the other with anxiety—remained significant in an independent dataset after robust correction for multiple testing. Both showed considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively) and support previously reported molecular biological findings.
Conclusion
Our approach detected novel specific genotype–phenotype relationships in BD that were missed by standard analyses like GWAS. While we developed and applied our method within the context of BD gene discovery, it may facilitate identifying highly specific genotype–phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts.