Kynurenine/Tryptophan ratio

Scope

Compute the kynurenine/tryptophan ratio (KTR), a marker of IDO activity and immune activation. Supports NA policies and verbose progress. Inputs must already be Kyn (nmol/L) and Trp (µmol/L); no unit conversion.

Background

The kynurenine/tryptophan ratio (KTR) quantifies the activity of indoleamine 2,3-dioxygenase 1 (IDO1), the rate-limiting enzyme in the kynurenine pathway of tryptophan catabolism. Elevated KTR reflects:

• Immune activation: IDO1 is upregulated by interferon-γ and other pro-inflammatory signals; high KTR indicates cell-mediated immune response.
• Immune escape: tumour cells exploit IDO1 to suppress T-cell activity; KTR is elevated in many malignancies.
• Ageing and inflammation: KTR rises with biological age and correlates with inflammatory burden (CRP, IL-6).

Formula: $\text{KTR} = \frac{\text{kynurenine (nmol/L)}}{\text{tryptophan (\mu mol/L)}}$

Approximate reference values in healthy adults:

Population	Typical KTR
Healthy adults (< 50 yr)	15–30
Older adults (> 65 yr)	25–45
Active infection / sepsis	80–400+
Cancer (some types)	50–200

Unit note: Kyn must be in nmol/L and Trp in µmol/L for the ratio to yield values in the physiological range. The resulting KTR is unitless (nmol/µmol).

Load packages and demo data

library(HealthMarkers)
library(tibble)

# Eight participants: healthy → chronically ill → acute infection range
df <- tibble::tibble(
  Kyn_nM = c(1200, 1800, 2500, 3200, 4500, 8000, 15000, 25000),
  Trp_uM = c(62,   50,   42,   38,   35,   28,   18,    12   )
)

Row interpretation: rows 1–2 ≈ healthy adults; rows 3–4 ≈ sub-clinical inflammation; rows 5–6 ≈ chronic immune activation; rows 7–8 ≈ acute infection or high-grade malignancy.

Column map (required)

col_map <- list(kynurenine = "Kyn_nM", tryptophan = "Trp_uM")

Core calculation

Default na_action = "keep": ratios are NA where inputs are missing; no extreme scan.

ktr <- kyn_trp_ratio(
  data = df,
  col_map = col_map,
  na_action = "keep",
  verbose = FALSE
)

ktr
#> # A tibble: 8 × 1
#>   kyn_trp_ratio
#>           <dbl>
#> 1          19.4
#> 2          36  
#> 3          59.5
#> 4          84.2
#> 5         129. 
#> 6         286. 
#> 7         833. 
#> 8        2083.

Extreme values

Extreme Kyn or Trp values will produce extreme KTR. Pre-filter implausible inputs before calling.

df_ext <- df
df_ext$Kyn_nM[2] <- 50000  # extreme; pre-filter
df_ext$Kyn_nM[df_ext$Kyn_nM > 20000] <- NA

ktr_filtered <- kyn_trp_ratio(
  data = df_ext,
  col_map = col_map,
  na_action = "warn",
  verbose = FALSE
)

ktr_filtered
#> # A tibble: 8 × 1
#>   kyn_trp_ratio
#>           <dbl>
#> 1          19.4
#> 2          NA  
#> 3          59.5
#> 4          84.2
#> 5         129. 
#> 6         286. 
#> 7         833. 
#> 8          NA

Missing data handling

keep/ignore/warn retain rows with NA ratios; omit drops rows with missing inputs; error stops on missingness.

df_na <- df
df_na$Trp_uM[3] <- NA

keep_out <- kyn_trp_ratio(df_na, col_map, na_action = "keep")
omit_out <- kyn_trp_ratio(df_na, col_map, na_action = "omit")

list(keep_rows = nrow(keep_out), omit_rows = nrow(omit_out))
#> $keep_rows
#> [1] 8
#> 
#> $omit_rows
#> [1] 7

Expectations

• Both markers must be mapped and present; non-numeric inputs are coerced with warnings if NAs are introduced.
• Trp must be positive; nonpositive values are set to NA with a warning.
• Output: one-column tibble kyn_trp_ratio; row count follows na_action if you omit rows.

Verbose diagnostics

old_opt <- options(healthmarkers.verbose = "inform")
kyn_trp_ratio(
  data    = df,
  col_map = col_map,
  verbose = TRUE
)
#> kyn_trp_ratio(): reading input 'df' — 8 rows × 2 variables
#> kyn_trp_ratio(): preparing inputs
#> kyn_trp_ratio(): col_map (2 columns — 2 specified)
#>   kynurenine        ->  'Kyn_nM'
#>   tryptophan        ->  'Trp_uM'
#> kyn_trp_ratio(): computing markers:
#>   kyn_trp_ratio  [kynurenine (nmol/L) / tryptophan (mumol/L)]
#> kyn_trp_ratio(): results: kyn_trp_ratio 8/8
#> # A tibble: 8 × 1
#>   kyn_trp_ratio
#>           <dbl>
#> 1          19.4
#> 2          36  
#> 3          59.5
#> 4          84.2
#> 5         129. 
#> 6         286. 
#> 7         833. 
#> 8        2083.
options(old_opt)

Column recognition (multi-biobank)

Kynurenine and tryptophan are measured by targeted HPLC or mass-spectrometry panels. Column names vary widely across platforms. Use hm_col_report() to check what is auto-detected in your dataset:

hm_col_report(your_data)  # shows matched keys and suggests col_map entries

See the Multi-Biobank Compatibility article for a full list of recognised synonyms (e.g., kynurenine_nmol_L, KYN, TRP, tryptophan_umol).

Tips

• Re-check units when ratios are very high (>100); Kyn should be nmol/L and Trp µmol/L.
• Reference: Badawy AA-B (2019). Tryptophan metabolism: a versatile area providing multiple targets for pharmacological intervention. Egypt J Basic Clin Pharmacol. https://doi.org/10.32527/2019/101415
• For modeling, consider scaling/transforming KTR separately after computation.