DNA barcoding reveals both known and novel taxa in the Albitarsis Group (Anopheles: Nyssorhynchus) of Neotropical malaria vectors

<p>Abstract</p> <p>Background</p> <p>Mosquitoes belonging to the Albitarsis Group (<it>Anopheles</it>: <it>Nyssorhynchus</it>) are of importance as malaria vectors across the Neotropics. The Group currently comprises six known species, and recent studies have indicated further hidden biodiversity within the Group. DNA barcoding has been proposed as a highly useful tool for species recognition, although its discriminatory utility has not been verified in closely related taxa across a wide geographic distribution.</p> <p>Methods</p> <p>DNA barcodes (658 bp of the mtDNA <it>Cytochrome c Oxidase </it>- <it>COI</it>) were generated for 565 <it>An. albitarsis </it>s.l. collected in Argentina, Brazil, Colombia, Paraguay, Trinidad and Venezuela over the past twenty years, including specimens from type series and type localities. Here we test the utility of currently advocated barcoding methodologies, including the Kimura-two-parameter distance model (K2P) and Neighbor-joining analysis (NJ), for determining species delineation within mosquitoes of the Neotropical Albitarsis Group of malaria vectors (<it>Anopheles</it>: <it>Nyssorhynchus</it>), and compare results with Bayesian analysis.</p> <p>Results</p> <p>Species delineation through barcoding analysis and Bayesian phylogenetic analysis, fully concur. Analysis of 565 sequences (302 unique haplotypes) resolved nine NJ tree clusters, with less than 2% intra-node variation. Mean intra-specific variation (K2P) was 0.009 (range 0.002 - 0.014), whereas mean inter-specific divergence were several-fold higher at 0.041 (0.020 - 0.056), supporting the reported "barcoding gap". These results show full support for separate species status of the six known species in the Albitarsis Group (<it>An. albitarsis </it>s.s., <it>An. albitarsis </it>F, <it>An. deaneorum</it>, <it>An. janconnae</it>, <it>An. marajoara </it>and <it>An. oryzalimnetes</it>), and also support species level status for two previously detected lineages - <it>An. albitarsis </it>G &<it>An. albitarsis </it>I (designated herein). In addition, we highlight the presence of a unique mitochondrial lineage close to <it>An. deaneorum </it>and <it>An. marajoara </it>(<it>An. albitarsis </it>H) from Rondônia and Mato Grosso in southwestern Brazil. Further integrated studies are required to confirm the status of this lineage.</p> <p>Conclusions</p> <p>DNA barcoding provides a reliable means of identifying both known and undiscovered biodiversity within the closely related taxa of the Albitarsis Group. We advocate its usage in future studies to elucidate the vector competence and respective distributions of all eight species in the Albitarsis Group and the novel mitochondrial lineage (<it>An. albitarsis </it>H) recovered in this study.</p

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

Background: Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. Approach: An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence-Based Laboratory Medicine Committee of the American Association for Clinical Chemistry jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. Content: In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A$_{1c}$ (HbA$_{1c}$) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of HbA$_{1c}$. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. Summary: The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended