GBA and APOE Impact Cognitive Decline in Parkinson's Disease: A 10-Year Population-Based Study.

BACKGROUND: Common genetic variance in apolipoprotein E (APOE), ß-glucocerebrosidase (GBA), microtubule-associated protein tau (MAPT), and α-synuclein (SNCA) has been linked to cognitive decline in Parkinson's disease (PD), although studies have yielded mixed results. OBJECTIVES: To evaluate the effect of genetic variants in APOE, GBA, MAPT, and SNCA on cognitive decline and risk of dementia in a pooled analysis of six longitudinal, non-selective, population-based cohorts of newly diagnosed PD patients. METHODS: 1002 PD patients, followed for up to 10 years (median 7.2 years), were genotyped for at least one of APOE-ε4, GBA mutations, MAPT H1/H2, or SNCA rs356219. We evaluated the effect of genotype on the rate of cognitive decline (Mini-Mental State Examanation, MMSE) using linear mixed models and the development of dementia (diagnosed using standardized criteria) using Cox regression; multiple comparisons were accounted for using Benjamini-Hochberg corrections. RESULTS: Carriers of APOE-ε4 (n = 281, 29.7%) and GBA mutations (n = 100, 10.3%) had faster cognitive decline and were at higher risk of progression to dementia (APOE-ε4, HR 3.57, P < 0.001; GBA mutations, HR 1.76, P = 0.001) than non-carriers. The risk of cognitive decline and dementia (HR 5.19, P < 0.001) was further increased in carriers of both risk genotypes (n = 23). No significant effects were observed for MAPT or SNCA rs356219. CONCLUSIONS: GBA and APOE genotyping could improve the prediction of cognitive decline in PD, which is important to inform the clinical trial selection and potentially to enable personalized treatment © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Impact of GBA1 variants on long-term clinical progression and mortality in incident Parkinson's disease.

INTRODUCTION: Variants in the GBA1 gene have been identified as a common risk factor for Parkinson's disease (PD). In addition to pathogenic mutations (those associated with Gaucher disease), a number of 'non-pathogenic' variants also occur at increased frequency in PD. Previous studies have reported that pathogenic variants adversely affect the clinical course of PD. The role of 'non-pathogenic' GBA1 variants on PD course is less clear. In this study, we report the effect of GBA1 variants in incident PD patients with long-term follow-up. METHODS: The study population consisted of patients in the Cambridgeshire Incidence of Parkinson's disease from General Practice to Neurologist and Parkinsonism: Incidence, Cognition and Non-motor heterogeneity in Cambridgeshire cohorts. Patients were grouped into non-carriers, carriers of 'non-pathogenic' GBA1 variants and carriers of pathogenic GBA1 mutations. Survival analyses for time to development of dementia, postural instability and death were carried out. Cox regression analysis controlling for potential confounders were used to determine the impact of GBA1 variants on these outcome measures. RESULTS: GBA1 variants were identified in 14.4% of patients. Pathogenic and 'non-pathogenic' GBA1 variants were associated with the accelerated development of dementia and a more aggressive motor course. Pathogenic GBA1 variants were associated with earlier mortality in comparison with non-carriers, independent of the development of dementia. DISCUSSION: GBA1 variants, including those not associated with Gaucher disease, are common in PD and result in a more aggressive disease course.

Motor complications in Parkinson's disease: 13-year follow-up of the CamPaIGN cohort.

BACKGROUND: Long-term population-representative data on motor fluctuations and levodopa-induced dyskinesias in Parkinson's disease is lacking. METHODS: The Cambridgeshire Parkinson's Incidence from GP to Neurologist (CamPaIGN) cohort comprises incident PD cases followed for up to 13 years (n = 141). Cumulative incidence of motor fluctuations and levodopa-induced dyskinesias and risk factors were assessed using Kaplan-Meyer and Cox regression analyses. RESULTS: Cumulative incidence of motor fluctuations and levodopa-induced dyskinesias was 54.3% and 14.5%, respectively, at 5 years and 100% and 55.7%, respectively, at 10 years. Higher baseline UPDRS-total and SNCA rs356219(A) predicted motor fluctuations, whereas higher baseline Mini-mental State Examination and GBA mutations predicted levodopa-induced dyskinesias. Early levodopa use did not predict motor complications. Both early motor fluctuations and levodopa-induced dyskinesias predicted reduced mortality in older patients (age at diagnosis >70 years). CONCLUSIONS: Our data support the hypothesis that motor complications are related to the severity of nigrostriatal pathology rather than early levodopa use and indicate that early motor complications do not necessarily confer a negative prognosis. © 2019 International Parkinson and Movement Disorder Society.

Dose finding for new vaccines: The role for immunostimulation/immunodynamic modelling.

Current methods to optimize vaccine dose are purely empirically based, whereas in the drug development field, dosing determinations use far more advanced quantitative methodology to accelerate decision-making. Applying these established methods in the field of vaccine development may reduce the currently large clinical trial sample sizes, long time frames, high costs, and ultimately have a better potential to save lives. We propose the field of immunostimulation/immunodynamic (IS/ID) modelling, which aims to translate mathematical frameworks used for drug dosing towards optimizing vaccine dose decision-making. Analogous to Pharmacokinetic/Pharmacodynamic (PK/PD) modelling, the mathematical description of drug distribution (PK) and effect (PD) in host, IS/ID modelling approaches apply mathematical models to describe the underlying mechanisms by which the immune response is stimulated by vaccination (IS) and the resulting measured immune response dynamics (ID). To move IS/ID modelling forward, existing datasets and further data on vaccine allometry and dose-dependent dynamics need to be generated and collate, requiring a collaborative environment with input from academia, industry, regulators, governmental and non-governmental agencies to share modelling expertise, and connect modellers to vaccine data.

Specifically neuropathic Gaucher's mutations accelerate cognitive decline in Parkinson's.

OBJECTIVE: We hypothesized that specific mutations in the ß-glucocerebrosidase gene (GBA) causing neuropathic Gaucher's disease (GD) in homozygotes lead to aggressive cognitive decline in heterozygous Parkinson's disease (PD) patients, whereas non-neuropathic GD mutations confer intermediate progression rates. METHODS: A total of 2,304 patients with PD and 20,868 longitudinal visits for up to 12.8 years (median, 4.1) from seven cohorts were analyzed. Differential effects of four types of genetic variation in GBA on longitudinal cognitive decline were evaluated using mixed random and fixed effects and Cox proportional hazards models. RESULTS: Overall, 10.3% of patients with PD and GBA sequencing carried a mutation. Carriers of neuropathic GD mutations (1.4% of patients) had hazard ratios (HRs) for global cognitive impairment of 3.17 (95% confidence interval [CI], 1.60-6.25) and a hastened decline in Mini-Mental State Exam scores compared to noncarriers (p = 0.0009). Carriers of complex GBA alleles (0.7%) had an HR of 3.22 (95% CI, 1.18-8.73; p = 0.022). By contrast, the common, non-neuropathic N370S mutation (1.5% of patients; HR, 1.96; 95% CI, 0.92-4.18) or nonpathogenic risk variants (6.6% of patients; HR, 1.36; 95% CI, 0.89-2.05) did not reach significance. INTERPRETATION: Mutations in the GBA gene pathogenic for neuropathic GD and complex alleles shift longitudinal cognitive decline in PD into "high gear." These findings suggest a relationship between specific types of GBA mutations and aggressive cognitive decline and have direct implications for improving the design of clinical trials. Ann Neurol 2016;80:674-685.

The role of tau in the pathological process and clinical expression of Huntington's disease.

Huntington's disease is a neurodegenerative disorder caused by an abnormal CAG repeat expansion within exon 1 of the huntingtin gene HTT. While several genetic modifiers, distinct from the Huntington's disease locus itself, have been identified as being linked to the clinical expression and progression of Huntington's disease, the exact molecular mechanisms driving its pathogenic cascade and clinical features, especially the dementia, are not fully understood. Recently the microtubule associated protein tau, MAPT, which is associated with several neurodegenerative disorders, has been implicated in Huntington's disease. We explored this association in more detail at the neuropathological, genetic and clinical level. We first investigated tau pathology by looking for the presence of hyperphosphorylated tau aggregates, co-localization of tau with mutant HTT and its oligomeric intermediates in post-mortem brain samples from patients with Huntington's disease (n = 16) compared to cases with a known tauopathy and healthy controls. Next, we undertook a genotype-phenotype analysis of a large cohort of patients with Huntington's disease (n = 960) with a particular focus on cognitive decline. We report not only on the tau pathology in the Huntington's disease brain but also the association between genetic variation in tau gene and the clinical expression and progression of the disease. We found extensive pathological inclusions containing abnormally phosphorylated tau protein that co-localized in some instances with mutant HTT. We confirmed this related to the disease process rather than age, by showing it is also present in two patients with young-onset Huntington's disease (26 and 40 years old at death). In addition we demonstrate that tau oligomers (suggested to be the most likely neurotoxic tau entity) are present in the Huntington's disease brains. Finally we highlight the clinical significance of this pathology by demonstrating that the MAPT haplotypes affect the rate of cognitive decline in a large cohort of patients with Huntington's disease. Our findings therefore highlight a novel important role of tau in the pathogenic process and clinical expression of Huntington's disease, which in turn opens up new therapeutic avenues for this incurable condition.

Genetic impact on cognition and brain function in newly diagnosed Parkinson's disease: ICICLE-PD study.

Parkinson's disease is associated with multiple cognitive impairments and increased risk of dementia, but the extent of these deficits varies widely among patients. The ICICLE-PD study was established to define the characteristics and prevalence of cognitive change soon after diagnosis, in a representative cohort of patients, using a multimodal approach. Specifically, we tested the 'Dual Syndrome' hypothesis for cognitive impairment in Parkinson's disease, which distinguishes an executive syndrome (affecting the frontostriatal regions due to dopaminergic deficits) from a posterior cortical syndrome (affecting visuospatial, mnemonic and semantic functions related to Lewy body pathology and secondary cholinergic loss). An incident Parkinson's disease cohort (n = 168, median 8 months from diagnosis to participation) and matched control group (n = 85) were recruited to a neuroimaging study at two sites in the UK. All participants underwent clinical, neuropsychological and functional magnetic resonance imaging assessments. The three neuroimaging tasks (Tower of London, Spatial Rotations and Memory Encoding Tasks) were designed to probe executive, visuospatial and memory encoding domains, respectively. Patients were also genotyped for three polymorphisms associated with cognitive change in Parkinson's disease and related disorders: (i) rs4680 for COMT Val158Met polymorphism; (ii) rs9468 for MAPT H1 versus H2 haplotype; and (iii) rs429358 for APOE-ε2, 3, 4. We identified performance deficits in all three cognitive domains, which were associated with regionally specific changes in cortical activation. Task-specific regional activations in Parkinson's disease were linked with genetic variation: the rs4680 polymorphism modulated the effect of levodopa therapy on planning-related activations in the frontoparietal network; the MAPT haplotype modulated parietal activations associated with spatial rotations; and APOE allelic variation influenced the magnitude of activation associated with memory encoding. This study demonstrates that neurocognitive deficits are common even in recently diagnosed patients with Parkinson's disease, and that the associated regional brain activations are influenced by genotype. These data further support the dual syndrome hypothesis of cognitive change in Parkinson's disease. Longitudinal data will confirm the extent to which these early neurocognitive changes, and their genetic factors, influence the long-term risk of dementia in Parkinson's disease. The combination of genetics and functional neuroimaging provides a potentially useful method for stratification and identification of candidate markers, in future clinical trials against cognitive decline in Parkinson's disease.

Glucocerebrosidase mutations influence the natural history of Parkinson's disease in a community-based incident cohort.

Carriers of mutations in the glucocerebrosidase gene (GBA) are at increased risk of developing Parkinson's disease. The frequency of GBA mutations in unselected Parkinson's disease populations has not been established. Furthermore, no previous studies have investigated the influence of GBA mutations on the natural history of Parkinson's disease using prospective follow-up. We studied DNA from 262 cases who had been recruited at diagnosis into one of two independent community-based incidence studies of Parkinson's disease. In 121 cases, longitudinal data regarding progression of motor disability and cognitive function were derived from follow-up assessments conducted every 18 months for a median of 71 months. Sequencing of the GBA was performed after two-stage polymerase chain reaction amplification. The carrier frequency of genetic variants in GBA was determined. Baseline demographic and clinical variables were compared between cases who were either GBA mutation carriers, polymorphism carriers or wild-type homozygotes. Cox regression analysis was used to model progression to major motor (Hoehn and Yahr stage 3), and cognitive (dementia) end-points in cases followed longitudinally. We show that in a representative, unselected UK Parkinson's disease population, GBA mutations are present at a frequency of 3.5%. This is higher than the prevalence of other genetic mutations currently associated with Parkinson's disease and indicates that GBA mutations make an important contribution to Parkinson's disease encountered in the community setting. Baseline clinical characteristics did not differ significantly between cases with and without GBA sequence variants. However, the hazard ratio for progression both to dementia (5.7, P = 0.003) and Hoehn and Yahr stage 3 (4.2, P = 0.003) were significantly greater in GBA mutation carriers. We also show that carriers of polymorphisms in GBA which are not generally considered to increase Parkinson's disease risk are at significantly increased risk of progression to Hoehn and Yahr stage 3 (3.2, P = 0.004). Our results indicate that genetic variation in GBA has an important impact on the natural history of Parkinson's disease. To our knowledge, this is the first time a genetic locus has been shown to influence motor progression in Parkinson's disease. If confirmed in further studies, this may indicate that GBA mutation status could be used as a prognostic marker in Parkinson's disease. Elucidation of the molecular mechanisms that underlie this effect will further our understanding of the pathogenesis of the disease and may in turn suggest novel therapeutic strategies.

Sexually transmitted infections on the border between Brazil and French Guiana.

Purpose: The border between the State of Amapa, Brazil, and French Guiana is mostly primary forest. In the Oyapock basin, socioeconomic circumstances have fueled sex work, gold mining and the circulation of sexually transmitted infections. Given the lack of comprehensive data on this border area, we describe the different sexually transmitted infections along the Brazil/French Guiana border and the testing and care activity. Methods: We conducted a review of the available scientific and technical literature on sexually transmitted infections in this complex border area. Temporal trends were graphed and for Human Immunodeficiency Virus (HIV) we estimated incidence using the European Center for prevention and Disease Control modeling tool. Results: Until 2019, 26 of the 46 HIV-infected patients followed and treated in Saint Georges de l'Oyapock were residing on the Brazilian side in Oiapoque. Virological suppression was only achieved for 75% of treated patients; but dropped to 62% during the COVID-19 epidemic. In 2019, cooperation efforts allowed HIV care in Oiapoque, resulting in the transfer of Brazilian patients previously followed on the French side and a substantial increase in the number of patients followed in Oiapoque. The average yearly HIV serological testing activity at the health center in Saint Georges was 16 tests per 100 inhabitants per year; in Camopi it was 12.2 per 100 inhabitants. Modeling estimated the number of persons living with HIV around 170 persons, corresponding to a prevalence of 0.54% and about 40 undiagnosed infections. The model also suggested that there were about 12 new infections per year in Saint Georges and Oiapoque, representing an HIV incidence rate of 3.8 cases per 10,000 per year. HPV prevalence in Saint Georges ranges between 25 and 30% and between 35 and 40% in Camopi. Testing activity for other sexually transmitted infections markedly increased in the past 5 years; the introduction of PCR for chlamydiasis and gonorrhea also had a substantial impact on the number of diagnoses. Conclusions: The ongoing cooperation between multiple partners on both sides of the border has led to remarkable progress in primary prevention, in testing efforts, in treatment and retention on both sides of the border. In a region with intense health professional turnover, nurturing cooperation and providing accurate assessments of the burden of sexually transmitted infections is essential to tackle a problem that is shared on both sides of the border.

Genetic and pathological links between Parkinson's disease and the lysosomal disorder Sanfilippo syndrome.

BACKGROUND: Parkinson's disease (PD) is a common neurodegenerative disorder of unknown etiology. The characteristic α-synuclein aggregation of PD is also a feature of Sanfilippo syndrome, a storage disorder caused by α-N-acetylglucosaminidase (NAGLU) gene mutations. We explored genetic links between these disorders and studied the pathology of Sanfilippo syndrome to investigate a common pathway toward α-synuclein aggregation. METHODS: We typed the 2 single-nucleotide polymorphisms that tag the common haplotypes of NAGLU in 926 PD patients and 2308 controls and also stained cortical tissue from 2 cases of Sanfilippo A syndrome using the anti-α-synuclein antibody, Per7. RESULTS: Allelic analysis showed an association between rs2071046 and risk for PD (P 1.3 × 10(-3) ). Intracellular α-synuclein accumulation was observed in the cortical tissue of both Sanfilippo A syndrome cases. CONCLUSIONS: This study suggests a possible role of NAGLU in susceptibility to PD while extending evidence for α-synuclein aggregation in the brain in lysosomal storage disorders. Our findings support a mechanism involving lysosomal dysfunction more generally in the pathogenesis of PD.

Identifying COVID-19 optimal vaccine dose using mathematical immunostimulation/immunodynamic modelling.

INTRODUCTION: Identifying optimal COVID-19 vaccine dose is essential for maximizing their impact. However, COVID-19 vaccine dose-finding has been an empirical process, limited by short development timeframes, and therefore potentially not thoroughly investigated. Mathematical IS/ID modelling is a novel method for predicting optimal vaccine dose which could inform future COVID-19 vaccine dose decision making. METHODS: Published clinical data on COVID-19 vaccine dose-response was identified and extracted. Mathematical models were calibrated to the dose-response data stratified by subpopulation, where possible to predict optimal dose. Predicted optimal doses were summarised across vaccine type and compared to chosen dose for the primary series of COVID-19 vaccines to identify vaccine doses that may benefit from re-evaluation. RESULTS: 30 clinical dose-response datasets in adults and elderly population were extracted for four vaccine types and optimal doses predicted using the models. Results suggest that, if re-assessed for dose, COVID-19 vaccines Ad26.cov, ChadOx1 n-Cov19, BNT162b2, Coronavac, and NVX-CoV2373 could benefit from increased dose in adults and mRNA-1273 and Coronavac, could benefit from increased and decreased dose for the elderly population, respectively. DISCUSSION: Future iterations of COVID-19 vaccines could benefit from re-evaluating dose to ensure most effective use of the vaccine and mathematical modelling can support this.

Mathematical Modelling for Optimal Vaccine Dose Finding: Maximising Efficacy and Minimising Toxicity.

Vaccination is a key tool to reduce global disease burden. Vaccine dose can affect vaccine efficacy and toxicity. Given the expense of developing vaccines, optimising vaccine dose is essential. Mathematical modelling has been suggested as an approach for optimising vaccine dose by quantitatively establishing the relationships between dose and efficacy/toxicity. In this work, we performed simulation studies to assess the performance of modelling approaches in determining optimal dose. We found that the ability of modelling approaches to determine optimal dose improved with trial size, particularly for studies with at least 30 trial participants, and that, generally, using a peaking or a weighted model-averaging-based dose-efficacy relationship was most effective in finding optimal dose. Most methods of trial dose selection were similarly effective for the purpose of determining optimal dose; however, including modelling to adapt doses during a trial may lead to more trial participants receiving a more optimal dose. Clinical trial dosing around the predicted optimal dose, rather than only at the predicted optimal dose, may improve final dose selection. This work suggests modelling can be used effectively for vaccine dose finding, prompting potential practical applications of these methods in accelerating effective vaccine development and saving lives.

The Correlated Beta Dose Optimisation Approach: Optimal Vaccine Dosing Using Mathematical Modelling and Adaptive Trial Design.

Mathematical modelling methods and adaptive trial design are likely to be effective for optimising vaccine dose but are not yet commonly used. This may be due to uncertainty with regard to the correct choice of parametric model for dose-efficacy or dose-toxicity. Non-parametric models have previously been suggested to be potentially useful in this situation. We propose a novel approach for locating optimal vaccine dose based on the non-parametric Continuous Correlated Beta Process model and adaptive trial design. We call this the 'Correlated Beta' or 'CoBe' dose optimisation approach. We evaluated the CoBe dose optimisation approach compared to other vaccine dose optimisation approaches using a simulation study. Despite using simpler assumptions than other modelling-based methods, we found that the CoBe dose optimisation approach was able to effectively locate the maximum efficacy dose for both single and prime/boost administration vaccines. The CoBe dose optimisation approach was also effective in finding a dose that maximises vaccine efficacy and minimises vaccine-related toxicity. Further, we found that these modelling methods can benefit from the inclusion of expert knowledge, which has been difficult for previous parametric modelling methods. This work further shows that using mathematical modelling and adaptive trial design is likely to be beneficial to locating optimal vaccine dose, ensuring maximum vaccine benefit and disease burden reduction, ultimately saving lives.

Optimising Vaccine Dose in Inoculation against SARS-CoV-2, a Multi-Factor Optimisation Modelling Study to Maximise Vaccine Safety and Efficacy.

Developing a vaccine against the global pandemic SARS-CoV-2 is a critical area of active research. Modelling can be used to identify optimal vaccine dosing; maximising vaccine efficacy and safety and minimising cost. We calibrated statistical models to published dose-dependent seroconversion and adverse event data of a recombinant adenovirus type-5 (Ad5) SARS-CoV-2 vaccine given at doses 5.0 × 1010, 1.0 × 1011 and 1.5 × 1011 viral particles. We estimated the optimal dose for three objectives, finding: (A) the minimum dose that may induce herd immunity, (B) the dose that maximises immunogenicity and safety and (C) the dose that maximises immunogenicity and safety whilst minimising cost. Results suggest optimal dose [95% confidence interval] in viral particles per person was (A) 1.3 × 1011 [0.8-7.9 × 1011], (B) 1.5 × 1011 [0.3-5.0 × 1011] and (C) 1.1 × 1011 [0.2-1.5 × 1011]. Optimal dose exceeded 5.0 × 1010 viral particles only if the cost of delivery exceeded £0.65 or cost per 1011 viral particles was less than £6.23. Optimal dose may differ depending on the objectives of developers and policy-makers, but further research is required to improve the accuracy of optimal-dose estimates.

Response Type and Host Species may be Sufficient to Predict Dose-Response Curve Shape for Adenoviral Vector Vaccines.

Vaccine dose-response curves can follow both saturating and peaking shapes. Dose-response curves for adenoviral vector vaccines have not been systematically described. In this paper, we explore the dose-response shape of published adenoviral animal and human studies. Where data were informative, dose-response was approximately five times more likely to be peaking than saturating. There was evidence that host species and response type may be sufficient for prediction of dose-response curve shape. Dose-response curve shape prediction could decrease clinical trial costs, accelerating the development of life-saving vaccines.

Immunologic Dose-Response to Adenovirus-Vectored Vaccines in Animals and Humans: A Systematic Review of Dose-Response Studies of Replication Incompetent Adenoviral Vaccine Vectors when Given via an Intramuscular or Subcutaneous Route.

Optimal vaccine dosing is important to ensure the greatest protection and safety. Analysis of dose-response data, from previous studies, may inform future studies to determine the optimal dose. Implementing more quantitative modelling approaches in vaccine dose finding have been recently suggested to accelerate vaccine development. Adenoviral vectored vaccines are in advanced stage of development for a variety of prophylactic and therapeutic indications, however dose-response has not yet been systematically determined. To further inform adenoviral vectored vaccines dose identification, historical dose-response data should be systematically reviewed. A systematic literature review was conducted to collate and describe the available dose-response studies for adenovirus vectored vaccines. Of 2787 papers identified by Medline search strategy, 35 were found to conform to pre-defined criteria. The majority of studies were in mice or humans and studied adenovirus serotype 5. Dose-response data were available for 12 different immunological responses. The majority of papers evaluated three dose levels, only two evaluated more than five dose levels. The most common dosing range was 107-1010 viral particles in mouse studies and 108-1011 viral particles in human studies. Data were available on adenovirus vaccine dose-response, primarily on adenovirus serotype 5 backbones and in mice and humans. These data could be used for quantitative adenoviral vectored vaccine dose optimisation analysis.

Using vaccine Immunostimulation/Immunodynamic modelling methods to inform vaccine dose decision-making.

Unlike drug dose optimisation, mathematical modelling has not been applied to vaccine dose finding. We applied a novel Immunostimulation/Immunodynamic mathematical modelling framework to translate multi-dose TB vaccine immune responses from mice, to predict most immunogenic dose in humans. Data were previously collected on IFN-γ secreting CD4+ T cells over time for novel TB vaccines H56 and H1 adjuvanted with IC31 in mice (1 dose groups (0.1-1.5 and 15 µg H56 + IC31), 45 mice) and humans (1 dose (50 µg H56/H1 + IC31), 18 humans). A two-compartment mathematical model, describing the dynamics of the post-vaccination IFN-γ T cell response, was fitted to mouse and human data, separately, using nonlinear mixed effects methods. We used these fitted models and a vaccine dose allometric scaling assumption, to predict the most immunogenic human dose. Based on the changes in model parameters by mouse H56 + IC31 dose and by varying the H56 dose allometric scaling factor between mouse and humans, we established that, at a late time point (224 days) doses of 0.8-8 µg H56 + IC31 in humans may be the most immunogenic. A 0.8-8 µg of H-series TB vaccines in humans, may be as, or more, immunogenic, as larger doses. The Immunostimulation/Immunodynamic mathematical modelling framework is a novel, and potentially revolutionary tool, to predict most immunogenic vaccine doses, and accelerate vaccine development.

Using Data from Macaques To Predict Gamma Interferon Responses after Mycobacterium bovis BCG Vaccination in Humans: a Proof-of-Concept Study of Immunostimulation/Immunodynamic Modeling Methods.

Macaques play a central role in the development of human tuberculosis (TB) vaccines. Immune and challenge responses differ across macaque and human subpopulations. We used novel immunostimulation/immunodynamic modeling methods in a proof-of-concept study to determine which macaque subpopulations best predicted immune responses in different human subpopulations. Data on gamma interferon (IFN-γ)-secreting CD4+ T cells over time after recent Mycobacterium bovis BCG vaccination were available for 55 humans and 81 macaques. Human population covariates were baseline BCG vaccination status, time since BCG vaccination, gender, and the monocyte/lymphocyte cell count ratio. The macaque population covariate was the colony of origin. A two-compartment mathematical model describing the dynamics of the IFN-γ T cell response after BCG vaccination was calibrated to these data using nonlinear mixed-effects methods. The model was calibrated to macaque and human data separately. The association between subpopulations and the BCG immune response in each species was assessed. The macaque subpopulations that best predicted immune responses in different human subpopulations were identified using Bayesian information criteria. We found that the macaque colony and the human baseline BCG status were significantly (P < 0.05) associated with the BCG-induced immune response. For humans who were BCG naïve at baseline, Indonesian cynomolgus macaques and Indian rhesus macaques best predicted the immune response. For humans who had already been BCG vaccinated at baseline, Mauritian cynomolgus macaques best predicted the immune response. This work suggests that the immune responses of different human populations may be best modeled by different macaque colonies, and it demonstrates the potential utility of immunostimulation/immunodynamic modeling to accelerate TB vaccine development.

Prediction of cognition in Parkinson's disease with a clinical-genetic score: a longitudinal analysis of nine cohorts.

BACKGROUND: Cognitive decline is a debilitating manifestation of disease progression in Parkinson's disease. We aimed to develop a clinical-genetic score to predict global cognitive impairment in patients with the disease. METHODS: In this longitudinal analysis, we built a prediction algorithm for global cognitive impairment (defined as Mini Mental State Examination [MMSE] ≤25) using data from nine cohorts of patients with Parkinson's disease from North America and Europe assessed between 1986 and 2016. Candidate predictors of cognitive decline were selected through a backward eliminated Cox's proportional hazards analysis using the Akaike's information criterion. These were used to compute the multivariable predictor on the basis of data from six cohorts included in a discovery population. Independent replication was attained in patients from a further three independent longitudinal cohorts. The predictive score was rebuilt and retested in 10 000 training and test sets randomly generated from the entire study population. FINDINGS: 3200 patients with Parkinson's disease who were longitudinally assessed with 27 022 study visits between 1986 and 2016 in nine cohorts from North America and Europe were assessed for eligibility. 235 patients with MMSE ≤25 at baseline and 135 whose first study visit occurred more than 12 years from disease onset were excluded. The discovery population comprised 1350 patients (after further exclusion of 334 with missing covariates) from six longitudinal cohorts with 5165 longitudinal visits over 12·8 years (median 2·8, IQR 1·6-4·6). Age at onset, baseline MMSE, years of education, motor exam score, sex, depression, and ß-glucocerebrosidase (GBA) mutation status were included in the prediction model. The replication population comprised 1132 patients (further excluding 14 patients with missing covariates) from three longitudinal cohorts with 19 127 follow-up visits over 8·6 years (median 6·5, IQR 4·1-7·2). The cognitive risk score predicted cognitive impairment within 10 years of disease onset with an area under the curve (AUC) of more than 0·85 in both the discovery (95% CI 0·82-0·90) and replication (95% CI 0·78-0·91) populations. Patients scoring in the highest quartile for cognitive risk score had an increased hazard for global cognitive impairment compared with those in the lowest quartile (hazard ratio 18·4 [95% CI 9·4-36·1]). Dementia or disabling cognitive impairment was predicted with an AUC of 0·88 (95% CI 0·79-0·94) and a negative predictive value of 0·92 (95% 0·88-0·95) at the predefined cutoff of 0·196. Performance was stable in 10 000 randomly resampled subsets. INTERPRETATION: Our predictive algorithm provides a potential test for future cognitive health or impairment in patients with Parkinson's disease. This model could improve trials of cognitive interventions and inform on prognosis. FUNDING: National Institutes of Health, US Department of Defense.