Natural selection favoring more transmissible HIV detected in United States molecular transmission network.

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters

General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv

The R package frailtySurv for simulating and fitting semi-parametric shared frailty models is introduced. Package frailtySurv implements semi-parametric consistent estimators for a variety of frailty distributions, including gamma, log-normal, inverse Gaussian and power variance function, and provides consistent estimators of the standard errors of the parameters' estimators. The parameters' estimators are asymptotically normally distributed, and therefore statistical inference based on the results of this package, such as hypothesis testing and confidence intervals, can be performed using the normal distribution. Extensive simulations demonstrate the flexibility and correct implementation of the estimator. Two case studies performed with publicly available datasets demonstrate applicability of the package. In the Diabetic Retinopathy Study, the onset of blindness is clustered by patient, and in a large hard drive failure dataset, failure times are thought to be clustered by the hard drive manufacturer and model

Clustered Multi-Task Learning: A Convex Formulation

In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from the others. In the context of learning linear functions for supervised classification or regression, this can be achieved by including a priori information about the weight vectors associated with the tasks, and how they are expected to be related to each other. In this paper, we assume that tasks are clustered into groups, which are unknown beforehand, and that tasks within a group have similar weight vectors. We design a new spectral norm that encodes this a priori assumption, without the prior knowledge of the partition of tasks into groups, resulting in a new convex optimization formulation for multi-task learning. We show in simulations on synthetic examples and on the IEDB MHC-I binding dataset, that our approach outperforms well-known convex methods for multi-task learning, as well as related non convex methods dedicated to the same problem

HIV transmission networks among transgender women in Los Angeles County, CA, USA: a phylogenetic analysis of surveillance data.

BackgroundTransgender women are among the groups at highest risk for HIV infection, with a prevalence of 27·7% in the USA; and despite this known high risk, undiagnosed infection is common in this population. We set out to identify transgender women and their partners in a molecular transmission network to prioritise public health activities.MethodsSince 2006, HIV protease and reverse transcriptase gene (pol) sequences from drug resistance testing have been reported to the Los Angeles County Department of Public Health and linked to demographic data, gender, and HIV transmission risk factor data for each case in the enhanced HIV/AIDS Reporting System. We reconstructed a molecular transmission network by use of HIV-TRAnsmission Cluster Engine (with a pairwise genetic distance threshold of 0·015 substitutions per site) from the earliest pol sequences from 22 398 unique individuals, including 412 (2%) self-identified transgender women. We examined the possible predictors of clustering with multivariate logistic regression. We characterised the genetically linked partners of transgender women and calculated assortativity (the tendency for people to link to other people with the same attributes) for each transmission risk group.Findings8133 (36·3%) of 22 398 individuals clustered in the network across 1722 molecular transmission clusters. Transgender women who indicated a sexual risk factor clustered at the highest frequency in the network, with 147 (43%) of 345 being linked to at least one other person (adjusted odds ratio [aOR] 2·0, p=0·0002). Transgender women were assortative in the network (assortativity 0·06, p<0·001), indicating that they tended to link to other transgender women. Transgender women were more likely than expected to link to other transgender women (OR 4·65, p<0·001) and cisgender men who did not identify as men who have sex with men (MSM; OR 1·53, p<0·001). Transgender women were less likely than expected to link to MSM (OR 0·75, p<0·001), despite the high prevalence of HIV among MSM. Transgender women were distributed across 126 clusters, and cisgender individuals linked to one transgender woman were 9·2 times more likely to link to a second transgender woman than other individuals in the surveillance database. Reconstruction of the transmission network is limited by sample availability, but sequences were available for more than 40% of diagnoses.InterpretationClustering of transgender women and the observed tendency for linkage with cisgender men who did not identify as MSM, shows the potential to use molecular epidemiology both to identify clusters that are likely to include undiagnosed transgender women with HIV and to improve the targeting of public health prevention and treatment services to transgender women.FundingCalifornia HIV and AIDS Research Program and National Institutes of Health-National Institute of Allergy and Infectious Diseases

Transmission of multidrug-resistant tuberculosis in the UK: a cross-sectional molecular and epidemiological study of clustering and contact tracing

BACKGROUND: Between 2000 and 2012 the number of multidrug-resistant (MDR) tuberculosis cases in the UK increased from 28 per year to 81 per year. We investigated the proportion of MDR tuberculosis cases arising from transmission in the UK and associated risk factors. METHOD: We identified patients with MDR tuberculosis notified in England, Wales, and Northern Ireland between Jan 1, 2004, and Dec 31, 2007, by linking national laboratory and surveillance data. Data for laboratory isolates, including drug sensitivities and 24-mycobacterial interspersed repetitive-unit-variable-number tandem repeat (MIRU-VNTR) typing were obtained routinely from the National Tuberculosis Reference laboratories as part of national tuberculosis surveillance. We investigated clusters of cases with indistinguishable MIRU-VNTR profiles to identify epidemiological links. We calculated transmission using the n-1 method and established associated risk factors by logistic regression. We also assessed the likelihood of transmission to additional secondary active tuberculosis cases, identified through conventional contact tracing. FINDINGS: 204 patients were diagnosed with MDR tuberculosis in the study period; 189 (92·6%) had an MIRU-VNTR profile. We identified 12 clusters containing 40 individuals and 149 unique strains. The proportion of cases attributable to recent transmission, on the basis of molecular data, was 15% (40 cases clustered-12 clusters/189 with a strain type). The proportion of cases attributable to recent transmission (ie, transmission within the UK) after adjustment for epidemiological links was 8·5% (22 cases with epidemiological links-six clusters/189 cases with a strain type). Being UK born (odds ratio 4·81; 95% CI 2·03-11·36, p=0·0005) and illicit drug use (4·75; 1·19-18·96, p=0·026) were significantly associated with clustering. The most common transmission setting was the household but 21 of 22 of epidemiological links were missed by conventional contact tracing. 13 secondary active tuberculosis cases identified by conventional contact tracing were mostly contacts of patients with MDR tuberculosis from countries of high tuberculosis burden. 11 (85%) of 13 shared the same country of birth as the index case, of whom ten did not share a strain type or drug resistance pattern. INTERPRETATION: Transmission of MDR tuberculosis in the UK is low and associated with being UK born or illicit drug use. MIRU-VNTR typing with cluster investigation was more successful at identifying transmission events than conventional contact tracing. Individuals with tuberculosis who have had contact with a known MDR tuberculosis source case from a country of high tuberculosis burden should have drug-sensitivity testing on isolates to ensure appropriate treatment is given. FUNDING: Public Health England