Table of Contents 1. Levels of evidence1.1 Reference2. Introduction3. Auditable targets4. Table summaries4.1 Initial diagnosis4.2 Assessment of ART‐naïve individuals4.3 ART initiation4.4 Initial assessment following commencement of ART4.5 Routine monitoring on ART4.6 References5. Newly diagnosed and transferring HIV‐positive individuals5.1 Initial HIV‐1 diagnosis5.2 Tests to determine whether acquisition of HIV infection is recent5.3 Individuals transferring care from a different HIV healthcare setting5.4 Communication with general practitioners and shared care5.5 Recommendations5.6 References6. Patient history6.1 Initial HIV‐1 diagnosis6.2 Monitoring of ART‐naïve patients6.3 Pre‐ART initiation assessment6.4 Monitoring individuals established on ART6.5 Assessment of adherence6.6 Recommendations6.7 References7. Examination7.1 Recommendations8. Identifying the need for psychological support8.1 References9. Assessment of immune status9.1 CD4 T cell counts9.2 CD4 T cell percentage9.3 References10. HIV viral load10.1 Initial diagnosis/ART naïve10.2 Post ART initiation10.3 Individuals established on ART10.4 Recommendations10.5 References11. Technical aspects of viral load testing11.1 References12. Viral load kinetics during ART and viral load ‘blips’12.1 References13. Proviral DNA load13.1 References14. Resistance testing14.1 Initial HIV‐1 diagnosis14.2 ART‐naïve14.3 Post treatment initiation14.4 ART‐experienced14.5 References15. Subtype determination15.1 Disease progression15.2 Transmission15.3 Performance of molecular diagnostic assays15.4 Response to therapy15.5 Development of drug resistance15.6 References16. Other tests to guide use of specific antiretroviral agents16.1 Tropism testing16.2 HLA B*5701 testing16.3 References17. Therapeutic drug monitoring17.1 Recommendations17.2 References18. Biochemistry testing18.1 Introduction18.2 Liver function18.3 Renal function18.4 Dyslipidaemia in HIV‐infected individuals18.5 Other biomarkers18.6 Bone disease in HIV‐infected patients18.7 References19. Haematology19.1 Haematological assessment and monitoring19.2 Recommendations19.3 References20. Serology20.1 Overview20.2 Hepatitis viruses20.3 Herpes viruses20.4 Measles and rubella20.5 Cytomegalovirus (CMV)20.6 References21. Other microbiological screening21.1 Tuberculosis screening21.2 Toxoplasma serology21.3 Tropical screening21.4 References22. Sexual health screening including anal and cervical cytology22.1 Sexual history taking, counselling and sexually transmitted infection (STI) screening22.2 Cervical and anal cytology22.3 Recommendations22.4 References23. Routine monitoring recommended for specific patient groups23.1 Women23.2 Older age23.3 Injecting drug users23.4 Individuals coinfected with HBV and HCV23.5 Late presenters23.6 References Appendix

BackgroundGenetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes.Methodology/Principal FindingsWe explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis.Conclusions/SignificanceThe eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this population.

Transmission of drug-resistant HIV-1 variants from antiretroviral treatment-experienced persons has been documented to occur through multiple routes, including sexual intercourse, intravenous drug use and vertically from mother to child. Newly infected persons with transmitted drug resistance (TDR) also act as a source for the onward transmission of resistant variants. Rates of virological suppression and behavioural patterns of treated populations and the relative fitness of drug-resistant variants are important determinants of the prevalence of TDR. Current estimates indicate that the prevalence is highest in regions and populations with long-established use of antiretroviral therapy. Limited data suggest that the incidence of TDR is rising in developing countries where access to therapy is increasing. There are methodological variations between studies, however, including those relative to the selection of the study population and the resistance interpretation system, which can skew prevalence estimates. TDR has important implications for the successful management of antiretroviral therapy. Routine resistance testing of drug-naive persons has been widely adopted in affluent countries and shown to effectively guide the selection of first-line regimens. Genotypic resistance tests offer a practical approach for detecting TDR. However, routine methods can only detect resistant mutants within the dominant quasi-species and fail to detect low-frequency resistant variants, which may become important once selective drug pressure is introduced. More sensitive testing methods are being evaluated but remain research tools at present. In addition, factors such as superinfection and possible differences in resistance patterns between plasma and cellular reservoirs and between anatomical compartments should be considered when evaluating TDR.

ObjectivesIt is still debated if pre-existing minority drug-resistant HIV-1 variants (MVs) affect the virological outcomes of first-line NNRTI-containing ART.MethodsThis Europe-wide case–control study included ART-naive subjects infected with drug-susceptible HIV-1 as revealed by population sequencing, who achieved virological suppression on first-line ART including one NNRTI. Cases experienced virological failure and controls were subjects from the same cohort whose viraemia remained suppressed at a matched time since initiation of ART. Blinded, centralized 454 pyrosequencing with parallel bioinformatic analysis in two laboratories was used to identify MVs in the 1%–25% frequency range. ORs of virological failure according to MV detection were estimated by logistic regression.ResultsTwo hundred and sixty samples (76 cases and 184 controls), mostly subtype B (73.5%), were used for the analysis. Identical MVs were detected in the two laboratories. 31.6% of cases and 16.8% of controls harboured pre-existing MVs. Detection of at least one MV versus no MVs was associated with an increased risk of virological failure (OR = 2.75, 95% CI = 1.35–5.60, P = 0.005); similar associations were observed for at least one MV versus no NRTI MVs (OR = 2.27, 95% CI = 0.76–6.77, P = 0.140) and at least one MV versus no NNRTI MVs (OR = 2.41, 95% CI = 1.12–5.18, P = 0.024). A dose–effect relationship between virological failure and mutational load was found.ConclusionsPre-existing MVs more than double the risk of virological failure to first-line NNRTI-based ART.

Objective To examine biological and social risk factors for meningococcal disease in adolescents. Design Prospective, population based, matched cohort study with controls matched for age and sex in 1:1 matching. Controls were sought from the general practitioner. Setting Six contiguous regions of England, which represent some 65% of the country's population. Participants 15-19 year olds with meningococcal disease recruited at hospital admission in six regions (representing 65% of the population of England) from January 1999 to June 2000, and their matched controls. Methods Blood samples and pernasal and throat swabs were taken from case patients at admission to hospital and from cases and matched controls at interview. Data on potential risk factors were gathered by confidential interview. Data were analysed by using univariate and multivariate conditional logistic regression. Results 144 case control pairs were recruited (74 male (51%); median age 17.6). 114 cases (79%) were confirmed microbiologically. Significant independent risk factors for meningococcal disease were history of preceding illness (matched odds ratio 2.9, 95% confidence interval 1.4 to 5.9), intimate kissing with multiple partners (3.7, 1.7 to 8.1), being a university student (3.4, 1.2 to 10) and preterm birth (3.7, 1.0 to 13.5). Religious observance (0.09, 0.02 to 0.6) and meningococcal vaccination (0.12, 0.04 to 0.4) were associated with protection. Conclusions Activities and events increasing risk for meningococcal disease in adolescence are different from in childhood. Students are at higher risk. Altering personal behaviours could moderate the risk. However, the development of further effective meningococcal vaccines remains a key public health priority.