Note: The following questionnaire is same as the one which was originally shared via Google doc [1]
We are expecting to have data from 30+ individuals on their response to Tdap boost. These will include individuals primed in infancy with either aP or wP. The data generated will be similar to what is described in our paper currently under review [2]. We will make information on the new sets of individuals available as described below in A. We will then ask each prediction team to make their best call on the questions asked in B. We will evaluate the answers to these questions using the metrics suggested in C.
A. Pre-vaccination Information to base the prediction on
Demographic data
- Age
- biological sex at birth
- vaccine priming status
Assays characterizing the immune status just before the vaccine is given (day 0)
- Antibody titers in plasma
- Secreted cytokine levels in plasma by OLINK
- Gene expression in PBMC by RNA-Seq
- Cell type frequencies in PBMC by cytometry
B. Immune responses to predict
B.1) Antibody titers
B.1.1) Rank the individuals by IgG antibody titers against pertussis antigens that we detect in plasma 14 days post booster vaccinations. Provide separate rankings for the individual pertussis antigens contained in the vaccine:
B.1.1.a) Pertussis toxin
B.1.1.b) FHA
B.1.1.c) Pertactin
B.1.2) What are the high vs. low antibody responders in terms of IgG subtypes at day 14 post boost? Provide separate rankings for individual antigens and IgG subtypes:
B.1.2.a) IgG1 - Pertussis toxin
B.1.2.b) IgG1 - FHA
B.1.2.c) IgG4 - Pertussis toxin
B.1.2.d) IgG4 - FHA
B.2) Cell Frequencies
Rank the individuals by predicted frequency of specific cell types on specific days after vaccination. Please provide separate rankings for
B.2.a) Plasmablast cells on day 7 post boost
B.2.b) CD4 TCM cells on 3 days post boost
B.2.c) Monocytes on day 1 post boost
B.3) Gene expression
Rank the individuals based on their predicted expression of specific genes at specific days post booster vaccination.
B.3.a) CCL3 on day 3 post boost
B.3.b) IL-6 on day 3 post boost
B.3.c) NFKBIA at day 7 post boost
B.3.d) XIST on day 14 post boost
C. Metrics
All predictions made will be in the form of ranking readouts from the highest response (=rank 1) to the lowest response in the N donors tested (=rank N). We will compare these to experimental readouts using
C.1) Spearman correlation
C.2) AUC value for an ROC curve where the top half of observed measurements are considered ‘positive’ and the lower half are considered ‘negative’
C.3) AUC value for an ROC curve where measurements will be considered positive if they are 3 standard deviations above the levels observed prior to boost
References
[1] The link for originally sent ‘Prediction task’ Google doc:
(https://docs.google.com/document/d/1v4pnyUt7ZVM1ZzhFZPOVfhPmZKPuWDFsTXXC4UT1_Ic/edit#)
[2] https://www.biorxiv.org/content/10.1101/2020.05.15.098830v1