Q (sonnet-5.5): Is there any study with a polygenic risk score?

▶ read_guide
{
 "uri": "cbioportal://clinical-data-guide"
}

◀ result
# Clinical Data Query Guide

## Overview
Clinical data in cBioPortal is stored at both patient and sample levels. Understanding the distinction is crucial for accurate analysis.

## Data Organization

### Patient-Level vs Sample-Level Data
- **Patient-level**: Demographics, overall survival, disease stage (stored once per patient)
- **Sample-level**: Sample type, sequencing platform, purity (can have multiple per patient)

### Key Tables
- `clinical_patient`: Patient-level clinical attributes
- `clinical_sample`: Sample-level clinical attributes
- `clinical_data_derived`: Pre-joined view combining both levels
- `clinical_attribute_meta`: Metadata about available clinical attributes

## Recommended Approach: Use clinical_data_derived

The `clinical_data_derived` table is pre-joined and optimized for most queries:

```sql
-- Get clinical data for specific attributes
SELECT
    sample_unique_id,
    patient_unique_id,
    attribute_name,
    attribute_value
FROM clinical_data_derived
WHERE
    cancer_study_identifier = 'your_study_id'
    AND attribute_name IN ('CANCER_TYPE', 'SAMPLE_TYPE', 'TMB_NONSYNONYMOUS');
```

## Clinical Attribute Discovery

### Use clinical_attribute_meta for Discovering Available Attributes
**Always start here** to see what clinical attributes are available for a specific study:

```sql
-- Discover available clinical attributes for a study
SELECT
    attr_id,
    description,
    patient_attribute,
    cancer_study_id
FROM clinical_attribute_meta
WHERE
    cancer_study_id = (
        SELECT cancer_study_id
        FROM cancer_study
        WHERE cancer_study_identifier = 'your_study_id'
    )
ORDER BY patient_attribute, attr_id;
```

**Key Fields:**
- **attr_id**: matches attr_id in clinical_sample/clinical_patient tables
- **description**: human-readable description of the attribute
- **patient_attribute**: true = patient attribute, false = sample attribute
- **cancer_study_id**: links to cancer_study table (filter by study)

## Attribute Semantics and Matching

### Case-Insensitive Matching for Attribute Values

Clinical values are free text across studies and may differ only by case. For example, a controlled-looking value such as germline mutation status may appear as `GERMLINE`, `Germline`, or another case variant.

When filtering `clinical_data_derived.attribute_value`, use case-insensitive matching unless you have already profiled the exact values in the target study:

```sql
-- Correct: case-insensitive clinical value filter
SELECT DISTINCT sample_unique_id, patient_unique_id
FROM clinical_data_derived
WHERE cancer_study_identifier = 'your_study_id'
  AND attribute_name = 'MUTATION_STATUS'
  AND upper(attribute_value) = 'GERMLINE';
```

Do not write `attribute_value = 'GERMLINE'` without first checking all distinct values for that attribute in the study.

### Query the Requested Attribute, Not a Proxy

Do not infer one clinical attribute from a related subtype or marker. Query the actual requested attribute when it … (17073 more chars)

▶ clickhouse_run_select_query
{
 "query": "SELECT cs.cancer_study_identifier, cs.name, m.attr_id, m.display_name, m.description
FROM clinical_attribute_meta m JOIN cancer_study cs ON cs.cancer_study_id = m.cancer_study_id
WHERE positionCaseInsensitive(m.attr_id,'PRS')>0 OR positionCaseInsensitive(m.attr_id,'POLYGENIC')>0 OR positionCaseInsensitive(m.display_name,'polygenic')>0 OR positionCaseInsensitive(m.description,'polygenic')>0 OR positionCaseInsensitive(m.display_name,'risk score')>0 OR positionCaseInsensitive(m.description,'risk score')>0
LIMIT 100"
}

◀ result
{"rows":[{"cancer_study_identifier":"mds_iwg_2022","name":"Myelodysplastic Syndromes (MDS IWG, IPSSM, NEJM Evidence 2022)","attr_id":"IPSSM_SCORE","display_name":"IPSS-M Score","description":"IPSS-M Risk Score"},{"cancer_study_identifier":"mds_iwg_2022","name":"Myelodysplastic Syndromes (MDS IWG, IPSSM, NEJM Evidence 2022)","attr_id":"IPSSR_SCORE","display_name":"IPSS-R Score","description":"IPSS-R Risk Score"},{"cancer_study_identifier":"coad_silu_2022","name":"Colon Cancer (Sidra-LUMC AC-ICAM, Nat Med 2023)","attr_id":"MBR_SCORE","display_name":"MBR Score","description":"Microbiome Risk Score calculated by the MBR classifier. The MBR classifier that was built by a relaxed multivariate elastic-net cox regression model including 41 genera"},{"cancer_study_identifier":"sft_sysucc_2023","name":"Solitary Fibrous Tumors (SYSUCC, Nat Commun 2023)","attr_id":"RISK_SCORE","display_name":"Total Risk Score","description":"Risk score calculated using nomogram integrated risk model based on mitotic count, density of Ki-67+ and CD163+ cells, and MTOR mutation. "},{"cancer_study_identifier":"prad_broad","name":"Prostate Adenocarcinoma (Broad/Cornell, Nat Genet 2012)","attr_id":"TMPRSS2_ERG_FUSION_STATUS","display_name":"TMPRSS2-ERG Fusion Status","description":"TMPRESS2-ERG fusion status."}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT cancer_study_identifier, name FROM cancer_study WHERE positionCaseInsensitive(description,'polygenic')>0 OR positionCaseInsensitive(name,'polygenic')>0 LIMIT 50"
}

◀ result
{"rows":[]}

═ answer (success)
I found no study in cBioPortal with a germline polygenic risk score (PRS). I searched clinical attribute names, display names and descriptions, plus study names and descriptions, for "PRS", "polygenic" and "risk score". I did not check generic-assay or other molecular profiles, so a PRS stored there wouldn't show up in this search.

A few studies do have other kinds of risk scores. None of them is a PRS:

| Study | Attribute | What it is |
|---|---|---|
| [Myelodysplastic Syndromes (MDS IWG, IPSSM, NEJM Evidence 2022)](https://www.cbioportal.org/study/summary?id=mds_iwg_2022) | IPSS-M Score and IPSS-R Score | Clinical prognostic risk scores for MDS |
| [Colon Cancer (Sidra-LUMC AC-ICAM, Nat Med 2023)](https://www.cbioportal.org/study/summary?id=coad_silu_2022) | MBR Score | Microbiome risk score from an elastic-net Cox model of 41 genera |
| [Solitary Fibrous Tumors (SYSUCC, Nat Commun 2023)](https://www.cbioportal.org/study/summary?id=sft_sysucc_2023) | Total Risk Score | Nomogram score based on mitotic count, Ki-67+ and CD163+ cell density, and MTOR mutation |

If you're after germline data more generally, I can look for studies with germline variant calls. I can also check for a PRS under a different name, such as a specific trait or a PGS Catalog ID, if you tell me what to search for.