rwe 0.1.1

Real World Evidence utilities and reporting

Real world evidence of siRNA targets

The current pipeline generates a real world genetic evidence document of an siRNA target by providing phenotypic details of individuals carrying predicted loss of function mutations in that target from multiple biobanks. The report can be used for the following three broader utilities:

• Discover new target-indication pairs
• Safety evaluation of potential target
• Repurposing opportunity of existing target

Description of the report

The package now supports two report modes:

• general
• participant_level

General report

The general report includes only cross-biobank and source-level summary evidence:

• Clinical records
• Labs and measurements
• Biomarkers
• Indication-specific reports

It does not include:

• Variant information
• Demographics
• Labs result profile images
• Survey information
• Homozygous loss of function carriers

Participant-level report

The participant-level report is biobank-specific and currently supports aou.

It includes:

• Variant information and demographics
• Labs and measurement figures
• Survey information
• Homozygous loss of function carriers

Future updates might have the following additional sections:

• OpenTargets
• Knowledge portal networks: https://hugeamp.org/research.html?pageid=kpn_portals
• Genomics England information: https://www.genomicsengland.co.uk/
• Genes and Health information: https://www.genesandhealth.org/
• Generate automated ppt report
• Link AI via api to generate summary of the indication specific section
• Use AI to generate ppt report for efficacy

Variant information and demographics

Variant information

Provides number of pLoF carriers across four variant categories in the All of Us cohort:

• stop gained
• frameshift
• splice acceptor
• splice donor

Demographics

Includes age, sex, ancestry and ethnicity information of pLoF carriers in comparison with non-carriers.

Clinical records

Provides phenomewide association study results of pLoF carriers in All of Us and UK Biobank cohorts. The All of Us association results are generated in-house. The UK Biobank results are collected from genebass and astrazeneca open-source portal.

Labs and measurements

Provides lab results of pLoF carriers in All of Us and UK Biobank cohort in comparison to the non-carriers. Detailed measurement definitions and concept IDs are maintained in docs/labs_and_measurements.md (included in the source distribution).

Survey information

Includes self-reported survey information about general, mental, physical and overall health of pLoF carriers in comparison with non-carriers in the All of Us cohort.

Homozygous loss of function carriers

Provides demographics and survey information of the biallelic lof variant carriers in All of Us.

Biomarkers

Provides association statistics of gene pLoF with plasma protein levels.

Indication specific report

Provides association results for user specified indications from All of Us and UK Biobank cohorts. Currently available indications are:

• obesity
• type_2_diabetes
• diabetic_kidney_disease
• dyslipidemia
• cold_agglutinin_disease
• long_qt_syndrome
• hypertrophic_cardiomyopathy
• metabolic_syndrome
• angelman_syndrome
• hemophilia
• essential_thrombocythemia
• aortic_valve_stenosis
• nash
• sepsis
• kidney_disease
• menopause
• noonan_syndrome

Resources used to generate the report

Controlled Datasets

All of Us

The All of Us cohort currently consists of 420k participants with whole genome sequencing and phenotypic data.

Open Source Databases

Here we describe the open source databases used for gathering evidence about the targets:

GeneBass

GeneBass reports phenomewide associations for LoF carriers among 380k participants from the UK Biobank cohort.

AstraZeneca PheWAS portal

AstraZeneca reports phenomewide associations for LoF carriers among 500k participants from the UK Biobank cohort.

Updates and Installation

Separately in TODO

Internal Use for installation

# upgrade packages for building
python -m pip install -U pip build
pip install twine

# New version packaging and upload
rm -rf dist build *.egg-info src/*.egg-info
# PowerShell:
Remove-Item -Recurse -Force dist, build, *.egg-info, src\*.egg-info
conda activate rwe
python -m build
pip install dist/rwe-0.1.1-py3-none-any.whl
python -c "from rwe.generate_report import generate_rwe_report; import rwe.clients.aou as aou; import rwe.clients.azn as azn; import rwe.clients.genebass as gbs; print('import ok')"
twine upload dist/*

# Before packaging environment test
conda install -c conda-forge python=3.12
pip install -r requirements.txt
playwright install
python -m playwright install-deps

Report configuration

The report generator now supports two explicit modes.

Example:

from rwe.generate_report import generate_rwe_report

generate_rwe_report(
    gene="PCSK9",
    chrm="1",
    mode="general",
    allofus=True,
    genebass=True,
    astrazeneca=True,
)

Participant-level example:

generate_rwe_report(
    gene="PCSK9",
    chrm="1",
    mode="participant_level",
    biobank="aou",
    generate_pptx=False,
)

Resources

1. ICD to Phecode mappings: https://www.vumc.org/wei-lab/sites/default/files/public_files/ICD_to_Phecode_mapping.csv
2. gnomAD v4.1 constriant metrics: https://gnomad.broadinstitute.org/data
3. phecodeX labels: https://github.com/PheWAS/PhecodeX
4. nptv carriers gnomad and genebass: Internal (Shicheng)
5. nptv carriers aou: Internal (Deepro)