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Sufyan Suleman

HealthMarkers

Clinical, metabolic and cardiovascular biomarker calculations in R

DocumentationSource on GitHubCite
R PACKAGEHealthMarkersClinical and cardiometabolicbiomarker calculations in RFor Researchers working withclinical trial or cohort datasufyansuleman.github.io

Overview

HealthMarkers is an R package that automates computation of derived clinical indices from laboratory and phenotypic data. Computing these indices by hand is slow, error-prone and rarely documented, so the package wraps over 290 validated biomarkers across multiple health domains behind a consistent interface, with automatic column recognition for 15+ cohorts including UK Biobank, NHANES, HUNT, Tromsø, FinnGen, Estonian Biobank, LifeLines and Generation Scotland.

Research problem

Researchers working with biobank or clinical trial data routinely need to re-derive standard indices (HOMA-IR, FIB-4, eGFR, PHQ-9 and similar) from raw measurements, but the formulas are scattered across papers, units differ between cohorts, and re-implementation introduces errors. HealthMarkers centralises these calculations with documented, published formulas.

What it computes

  • Insulin sensitivity: fasting_is(), ogtt_is(), adipo_is(), all_insulin_indices(), HOMA-IR, QUICKI, Matsuda, Stumvoll, Gutt and 40+ related indices
  • Glycemic: glycemic_markers(), TyG index, METS-IR, LAR, ASI, HOMA-CP
  • Lipid/atherogenic: lipid_markers(), cvd_marker_aip(), TC/HDL ratio, AIP, CRI-I/II, Castelli index, LDL particle estimates
  • Liver: liver_markers(), liver_fat_markers(), FLI, NFS, FIB-4, APRI, BARD, ALBI, MELD-XI, HSI, LAP
  • Renal/CKD: renal_markers(), kidney_failure_risk(), ckd_stage(), eGFR, KFRE, CKD staging, UACR, FE-Urea
  • Cardiovascular risk: cvd_risk_ascvd(), cvd_risk_qrisk3(), cvd_risk_scorescvd(), ASCVD (PCE), QRISK3, SCORE2/SCORE2-OP
  • Pulmonary: spirometry_markers(), pulmo_markers(), bode_index(), FEV1/FVC z-scores, GLI 2012, BODE index
  • Inflammatory/ageing: inflammatory_markers(), iAge(), oxidative_markers(), NLR, PLR, SII, LMR, iAge clock, 8-OHdG, KTR
  • Hormonal: hormone_markers(), T/E2 ratio, TSH/fT4, cortisol/DHEA, LH/FSH, HOMA-B, FAI
  • Body composition: obesity_indices(), adiposity_sds(), alm_bmi_index(), BMI, WHR, ABSI, BRI, BAI, SDS z-scores
  • Bone/fracture: bone_markers(), frax_score(), P1NP, osteocalcin, CTX, NTX, FRAX probabilities
  • Frailty/comorbidity: frailty_index(), charlson_index(), sarc_f_score(), Rockwood index, Charlson CCI, SARC-F
  • Vitamins/nutrients: vitamin_markers(), nutrient_markers(), vitamin D status, B12/folate ratio, ferritin saturation
  • Alternate biofluids: saliva_markers(), sweat_markers(), urine_markers(), CAR, sweat chloride, urinary ratios
  • Psychiatric: psych_markers(), phq9_score(), gad7_score(), k10_score(), PHQ-9, GAD-7, ISI, GHQ-12, K10, WHO-5, ASRS, BIS-11, SPQ
  • Neurological: nfl_marker(), kyn_trp_ratio(), age-adjusted NfL, kynurenine/tryptophan ratio
  • Dispatcher: all_health_markers(), runs any combination of the 40+ marker groups on a single wide tibble

Install

install.packages("HealthMarkers")

# development version
remotes::install_github("sufyansuleman/HealthMarkers")

Documentation

Full reference and vignettes: https://sufyansuleman.github.io/HealthMarkers/



Do you have data with hundreds of variables and need the standard indices out of it?

HealthMarkers computes over 290 of them from a single table. I can help you map your columns, choose the right markers, and run it on your cohort.

Get in touch