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Compute tracer/DXA-based insulin sensitivity indices

Source: R/tracer_dxa_is.R
tracer_dxa_is.Rd

Uses stable isotope tracer infusion rates and DXA-measured fat mass to compute peripheral and adipose insulin sensitivity and related metrics.

Usage

tracer_dxa_is(
  data,
  col_map = NULL,
  normalize = NULL,
  na_action = c("keep", "omit", "error"),
  na_warn_prop = 0.2,
  verbose = TRUE
)

Arguments

data

A data.frame or tibble containing raw measurements.

col_map

Named list with entries (depending on mode): Adipose-only required: - I0: fasting insulin (pmol/L) - rate_glycerol, rate_palmitate: tracer rates (mumol/min) - fat_mass, weight, bmi: body composition - HDL_c: HDL cholesterol (mmol/L) Full mode additionally requires: - G0, G30, G120: glucose (mmol/L) - I30, I120: insulin (pmol/L) - TG: triglycerides (mmol/L) - FFA: free fatty acids (mmol/L)

normalize

Ignored (kept for backward compatibility).

na_action

One of c("keep","omit","error") for NA handling on required inputs. Default "keep".

na_warn_prop

Proportion \([0,1]\) to trigger high-missingness warnings on required inputs. Default 0.2.

verbose

Logical; if TRUE, prints progress messages and a completion summary.

Value

  • Adipose-only tibble columns: LIRI_inv, Lipo_inv, ATIRI_inv

  • Full-mode tibble columns: I_AUC, FFA_AUC, tracer_palmitate_SI, tracer_glycerol_SI, LIRI_inv, Lipo_inv, ATIRI_inv

Details

Modes:

  • Adipose-only indices when only adipose-related keys are mapped (no OGTT glucose/insulin time series)

  • Full indices otherwise

Expected units:

  • Glucose: mmol/L (internally converted to mg/dL when needed)

  • Insulin: pmol/L (internally converted to muU/mL via /6)

  • TG: mmol/L (to mg/dL via *88.57); HDL-c: mmol/L (to mg/dL via *38.67)

  • Tracer rates: mumol/min

  • Fat mass, weight: kg; BMI: kg/m^2

Note

tracer_palmitate_SI and tracer_glycerol_SI are simple rate/fat_mass ratios; the Steele (1959) non-steady-state tracer equation is not implemented here. The LIRI formula coefficients (-0.091, 0.4, 0.346, -0.408, 0.435) are attributed to Gastaldelli et al. but the paper cited (gastaldelli2004betacell) covers beta-cell dysfunction, not LIRI derivation; the primary LIRI source should be verified. In adipose-only mode (I30 absent) the mean-insulin term uses I0 twice as a fallback.

References

Groop LC, Bonadonna RC, Simonson DC, et al. (1989). “Different Effects of Insulin and Oral Hypoglycemic Agents on Glucose and Lipid Metabolism in Type II Diabetes.” Journal of Clinical Investigation, 84(2), 578–585. doi:10.1172/JCI114142 . (tracer lipolysis methodology; background) Steele R (1959). “Influences of Glucose Loading and of Injected Insulin on Hepatic Glucose Output.” Annals of the New York Academy of Sciences, 82(2), 420–430. doi:10.1111/j.1749-6632.1959.tb44923.x . (tracer dilution theory; Steele equation not directly implemented — background) Roden M, Price TB, Perseghin G, et al. (1996). “Mechanism of Free Fatty Acid-Induced Insulin Resistance in Humans.” Journal of Clinical Investigation, 97(12), 2859–2865. doi:10.1172/JCI118742 . (FFA-induced insulin resistance mechanism; background) Gastaldelli A, Ferrannini E, Miyazaki Y, Matsuda M, DeFronzo RA (2004). “Beta-Cell Dysfunction and Glucose Intolerance: Results from the San Antonio Metabolism Study.” Diabetologia, 47(1), 31–39. doi:10.1007/s00125-003-1263-9 . (beta-cell dysfunction context; LIRI formula source unverified — background) Karpe F, Dickmann JR, Frayn KN (2011). “Fatty Acids, Obesity, and Insulin Resistance: Time for a Reevaluation.” Diabetes, 60(10), 2441–2449. doi:10.2337/db11-0425 . (FFA and insulin resistance review; background) Petersen KF, Dufour S, Savage DB, et al. (2007). “The Role of Skeletal Muscle Insulin Resistance in the Pathogenesis of the Metabolic Syndrome.” Proceedings of the National Academy of Sciences, 104(31), 12587–12594. doi:10.1073/pnas.0705408104 . (muscle insulin resistance and metabolic syndrome; background) Santomauro AT, Boden G, Silva ME, et al. (1999). “Overnight Lowering of Free Fatty Acids with Acipimox Improves Insulin Resistance and Glucose Tolerance in Obese Diabetic and Nondiabetic Subjects.” Diabetes, 48(9), 1836–1841. doi:10.2337/diabetes.48.9.1836 . (FFA lowering and insulin sensitivity; background)

Examples

df <- data.frame(
  I0 = c(60, 75), rate_glycerol = c(2.1, 2.8), rate_palmitate = c(1.8, 2.3),
  fat_mass = c(18, 24), weight = c(72, 85), BMI = c(24, 29),
  HDL_c = c(1.3, 1.1)
)
col_map <- list(I0="I0", rate_glycerol="rate_glycerol",
                rate_palmitate="rate_palmitate", fat_mass="fat_mass",
                weight="weight", bmi="BMI", HDL_c="HDL_c")
tracer_dxa_is(df, col_map = col_map)
#> tracer_dxa_is(): reading input 'df' — 2 rows × 7 variables
#> tracer_dxa_is(): preparing inputs
#> tracer_dxa_is(): col_map (7 columns — 7 specified)
#>   I0                ->  'I0'
#>   rate_glycerol     ->  'rate_glycerol'
#>   rate_palmitate    ->  'rate_palmitate'
#>   fat_mass          ->  'fat_mass'
#>   weight            ->  'weight'
#>   bmi               ->  'BMI'
#>   HDL_c             ->  'HDL_c'
#> tracer_dxa_is(): computing markers:
#>   LIRI_inv, Lipo_inv, ATIRI_inv
#> tracer_dxa_is(): adipose-only indices
#> tracer_dxa_is(): results: LIRI_inv 2/2, Lipo_inv 2/2, ATIRI_inv 2/2
#> # A tibble: 2 × 3
#>   LIRI_inv Lipo_inv ATIRI_inv
#>      <dbl>    <dbl>     <dbl>
#> 1    -1.01      -21     -18  
#> 2    -1.13      -35     -28.7