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BACKGROUND/OBJECTIVE: To synchronize data collection, the National Institute of Neurological Disorders and Stroke recommended Common Data Elements (CDEs) for use in Parkinson’s disease (PD) research. This study delineated the progression patterns of these CDEs in a cohort of PD patients. METHODS: One hundred-twenty-five PD patients participated in the PD Biomarker Program (PDBP) at Penn State. CDEs, including MDS-Unified PD Rating Scales (UPDRS)-total, questionnaire-based non-motor (-I) and motor (-II), and rater-based motor (-III) subscales; Montreal Cognitive Assessment (MoCA); Hamilton Depression Rating Scale (HDRS); University of Pennsylvania Smell Identification Test (UPSIT); and PD Questionnaire (PDQ-39) were obtained at baseline and three annual follow-ups. Annual change was delineated for PD or subgroups [early=PDE, disease duration (DD)5 y] using mixed effects model analyses. RESULTS: UPDRS-total, -II, and PDQ-39 scores increased significantly, and UPSIT decreased, whereas UPDRS-I, -III, MoCA, and HDRS did not change, over 36 months in the overall PD cohort. In the PDE subgroup, UPDRS-II increased and UPSIT decreased significantly, whereas MoCA and UPSIT decreased significantly in the PDM subgroup. In the PDL subgroup, UPDRS-II and PDQ-39 increased significantly. Other metrics within each individual subgroup did not change. Sensitivity analyses using subjects with complete data confirmed these findings. CONCLUSIONS: Among CDEs, UPDRS-total, –II, PDQ-39, and UPSIT all are sensitive metrics to track PD progression. Subgroup analyses revealed that these CDEs have distinct stage-dependent sensitivities, with UPSIT for DD5 y, UPDRS-II for early (DD 5).

Stimulating broadly neutralizing antibodies (bnAbs) directly from germline remains a barrier for HIV vaccines. HIV superinfection elicits bnAbs more frequently than single infection, providing clues of how to elicit such responses. We used longitudinal antibody sequencing and structural studies to characterize bnAb development from a superinfection case. BnAb QA013.2 bound initial and superinfecting viral Env, despite its probable naive progenitor only recognizing the superinfecting strain, suggesting both viruses influenced this lineage. A 4.15 Å cryo-EM structure of QA013.2 bound to native-like trimer showed recognition of V3 signatures (N301/N332 and GDIR). QA013.2 relies less on CDRH3 and more on framework and CDRH1 for affinity and breadth compared to other V3/glycan-specific bnAbs. Antigenic profiling revealed that viral escape was achieved by changes in the structurally-defined epitope and by mutations in V1. These results highlight shared and novel properties of QA013.2 relative to other V3/glycan-specific bnAbs in the setting of sequential, diverse antigens.

Stimulating broadly neutralizing antibodies (bnAbs) directly from germline remains a barrier for HIV vaccines. HIV superinfection elicits bnAbs more frequently than single infection, providing clues of how to elicit such responses. We used longitudinal antibody sequencing and structural studies to characterize bnAb development from a superinfection case. Mature bnAb QA013.2 bound both initial transmitted and superinfecting virus, but its inferred naïve bound only the superinfecting strain and was not neutralizing. QA013.2 requires residues spanning FWRH1-CDRH1 to attain breadth, which is uncommon for V3-specific bnAbs. A 4.15 Å cryo-EM structure of QA013.2 bound to heterologous native-like trimer showed recognition of V3 signatures (N301, N332, and GDIR). Antigenic profiling revealed that viral escape was achieved not only by changes in the structurally-defined epitope, but also by mutations in V1. These results highlight shared and distinct properties of QA013.2 relative to other V3-specific bnAbs in the setting of sequential, diverse antigenic variants.

Stimulating broadly neutralizing antibodies (bnAbs) directly from germline remains a barrier for HIV vaccines. HIV superinfection elicits bnAbs more frequently than single infection, providing clues of how to elicit such responses. We used longitudinal antibody sequencing and structural studies to characterize bnAb development from a superinfection case. Mature bnAb QA013.2 bound both initial transmitted and superinfecting virus, but its inferred naïve bound only the superinfecting strain and was not neutralizing. QA013.2 requires residues spanning FWRH1-CDRH1 to attain breadth, which is uncommon for V3-specific bnAbs. A 4.15 Å cryo-EM structure of QA013.2 bound to heterologous native-like trimer showed recognition of V3 signatures (N301, N332, and GDIR). Antigenic profiling revealed that viral escape was achieved not only by changes in the structurally-defined epitope, but also by mutations in V1. These results highlight shared and distinct properties of QA013.2 relative to other V3-specific bnAbs in the setting of sequential, diverse antigenic variants.

Summary and statement of need The analysis of human pathogens requires a diverse collection of bioinformatics tools. These tools include standard genomic and phylogenetic software and custom software developed to handle the relatively numerous and short genomes of viruses and bacteria. Researchers increasingly depend on the outputs of these tools to infer transmission dynamics of human diseases and make actionable recommendations to public health officials (Black et al., 2020; Gardy et al., 2015). In order to enable real-time analyses of pathogen evolution, bioinformatics tools must scale rapidly with the number of samples and be flexible enough to adapt to a variety of questions and organisms. To meet these needs, we developed Augur, a bioinformatics toolkit designed for phylogenetic analyses of human pathogens.

A prerequisite for the design of an HIV vaccine that elicits protective antibodies is understanding the developmental pathways that result in desirable antibody features. The development of antibodies that mediate antibody-dependent cellular cytotoxicity (ADCC) is particularly relevant because such antibodies have been associated with HIV protection in humans. We reconstructed the developmental pathways of six human HIV-specific ADCC antibodies using longitudinal antibody sequencing data. Most of the inferred naive antibodies did not mediate detectable ADCC. Gain of antigen binding and ADCC function typically required mutations in complementarity determining regions of one or both chains. Enhancement of ADCC potency often required additional mutations in framework regions. Antigen binding affinity and ADCC activity were correlated, but affinity alone was not sufficient to predict ADCC potency. Thus, elicitation of broadly active ADCC antibodies may require mutations that enable high-affinity antigen recognition along with mutations that optimize factors contributing to functional ADCC activity., eLife digest Nearly four decades after the human immunodeficiency virus (HIV for short) was first identified, the search for a vaccine still continues. An effective immunisation would require elements that coax the human immune system into making HIV-specific antibodies – the proteins that can recognise, bind to and deactivate the virus. Crucially, antibodies can also help white blood cells to target and destroy cells infected with HIV. This ‘antibody-dependent cellular cytotoxicity’ could be a key element of a successful vaccine, yet it has received less attention than the ability for antibodies to directly neutralize the virus. In particular, it is still unclear how antibodies develop the ability to flag HIV-infected cells for killing. Indeed, over the course of an HIV infection, an immune cell goes through genetic changes that tweak the 3D structure of the antibodies it manufactures. This process can improve the antibodies' ability to fight off the virus, but it was still unclear how it would shape antibody-dependent cellular cytotoxicity. To investigate this question, Doepker et al. retraced how the genes coding for six antibody families changed over time in an HIV-carrying individual. This revealed that antibodies could not initially trigger antibody-dependent cellular cytotoxicity. The property emerged and improved thanks to two types of alterations in the genetic sequences. One set of changes increased how tightly the antibodies could bind to the virus, targeting sections of the antibodies that can often vary. The second set likely altered the 3D structure in others ways, potentially affecting how antibodies bind the virus or how they interact with components of the immune system that help to kill HIV-infected cells. These alterations took place in segments of the antibodies that undergo less change over time. Ultimately, the findings by Doepker et al. suggest that an efficient HIV vaccine may rely on helping antibodies to evolve so they can bind more tightly to the virus and trigger cellular cytotoxicity more strongly.

Probabilistic models of adaptive immune repertoire sequence distributions can be used to infer the expansion of immune cells in response to stimulus, differentiate genetic from environmental factors that determine repertoire sharing, and evaluate the suitability of various target immune sequences for stimulation via vaccination. Classically, these models are defined in terms of a probabilistic V(D)J recombination model which is sometimes combined with a selection model. In this paper we take a different approach, fitting variational autoencoder (VAE) models parameterized by deep neural networks to T cell receptor (TCR) repertoires. We show that simple VAE models can perform accurate cohort frequency estimation, learn the rules of VDJ recombination, and generalize well to unseen sequences. Further, we demonstrate that VAE-like models can distinguish between real sequences and sequences generated according to a recombination-selection model, and that many characteristics of VAE-generated sequences are similar to those of real sequences.