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Biochemical and brain heterogeneity characterizes psychiatric and non-psychiatric illness.

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The authors' code

R · 69 lines · 2 KB · no license

  2. # GAMLSS Z-score Calculation Script for Biochemical Data (SHASH Distribution)
  3. # Author: Maria Di Biase
  4. # Description: This script fits a GAMLSS model using the SHASH distribution
  5. # and computes z-scores for all subjects in the dataset based on predicted
  6. # distribution parameters (mu, sigma, nu, tau).
  8. rm(list = ls())
  10. # Load necessary libraries
  11. library(gamlss)
  12. library(R.matlab)
  13. library(pracma)
  15. # Set working directory
  16. setwd("GAMLSS_input_biochem/")
  18. # Define output path
  19. PATH_OUT <- "GAMLSS_output/"
  21. # Define the biochemical measure
  22. biochem_measure <- 'Eosinophill_percentage'
  23. FN <- paste("GAMLSSinput_Biochem_", biochem_measure, ".mat", sep="")
  25. # Load input data
  26. M <- readMat(FN)
  27. biochem_measure_data <- as.data.frame(M$biochem.measure)
  28. mydata_tmp <- as.data.frame(cbind(M$AGE, M$SEX, M$data))
  29. names(mydata_tmp) <- c("age", "sex", "phenotype")
  31. # Filter healthy controls
  32. ind <- which(M$DX[,1] %in% c(1))
  33. mydata <- mydata_tmp[ind, ]
  35. # Fit the GAMLSS model
  36. fam_dist <- 'SHASH'
  37. mdl <- gamlss(phenotype ~ fp(age, npoly=1) + sex,
  38. sigma.fo = ~fp(age, npoly=1),
  39. family = fam_dist,
  40. data = mydata,
  41. robust = TRUE)
  43. # Generate z-scores for all subjects
  44. n <- nrow(mydata_tmp)
  45. z_scores <- rep(NA, n)
  46. p <- rep(NA, n)
  48. for (sub in 1:n) {
  49. sub_data <- data.frame(age = mydata_tmp$age[sub],
  50. sex = mydata_tmp$sex[sub],
  51. phenotype = mydata_tmp$phenotype[sub])
  53. # Predict parameters
  54. params <- predictAll(mdl, newdata = sub_data)
  56. # Calculate CDF value for observed phenotype
  57. p[sub] <- pSHASH(mydata_tmp$phenotype[sub],
  58. mu = params$mu,
  59. sigma = params$sigma,
  60. nu = params$nu,
  61. tau = params$tau)
  63. # Convert CDF to z-score using standard normal inverse
  64. z_scores[sub] <- qNO(p[sub])
  65. }
  67. # Export results
  68. output_file <- paste(PATH_OUT, "GAMLSSout_main_ZSCORES", biochem_measure, ".mat", sep = "")
  69. writeMat(output_file, z_scores_unseen_subs = z_scores)

gamlss_zscore.R at commit 512b732, no license · at the source

Overview

Authors: Maria A. Di Biase1,2,3, William R. Reay4, Hadis Jameei1, Yuanzhe Liu1, Ye E. Tian1, Elysha Ringin1, Susan Rossell5,6, James A. Karantonis1,5, Tamsyn E. Van Rheenen1,5, Junhao Wen7, Christos Pantelis1,8,9, Andrew Zalesky1,10
ORCID iDs: Maria A. Di Biase, William R. Reay, Yuanzhe Liu, Ye E. Tian, Elysha Ringin, Tamsyn E. Van Rheenen, Junhao Wen, Christos Pantelis, Andrew Zalesky
  1. Department of Psychiatry, Melbourne Medical School, The University of Melbourne,Melbourne, VIC Australia
  2. Department of Anatomy and Physiology, School of Biomedical Sciences, The University of Melbourne,Melbourne, VIC Australia
  3. Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School,Boston, MA USA
  4. Menzies Institute for Medical Research, University of Tasmania,Hobart, TAS Australia
  5. Centre for Mental Health and Brain Sciences, Swinburne University,Melbourne, VIC Australia
  6. InsideOut Institute, University of Sydney and Sydney Local Health District,Sydney, NSW Australia
  7. Laboratory of AI and Biomedical Science (LABS), Columbia University,New York, NY USA
  8. Western Centre for Health Research & Education (WCHRE), University of Melbourne & Western Health, Sunshine Hospital,St. Albans, VIC Australia
  9. Monash Institute of Pharmaceutical Sciences (MIPS), Monash University,Melbourne, Australia
  10. Faculty of Engineering and Information Technology, The University of Melbourne,Melbourne, VIC Australia
Institutions: The University of Melbourne (Australia); Brigham and Women's Hospital (United States); University of Tasmania (Australia); Swinburne University of Technology (Australia); The University of Sydney (Australia); Columbia University (United States); Monash University (Australia)
Journal: Nature communications, volume 17, issue 1, article 6235
Dates: received 26 August 2025; accepted 16 April 2026; published online 8 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41467-026-72604-4 · PMID 42103728 · PMCID PMC13369505 · OpenAlex W7160716036
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), schizophrenia / psychosis (population), clinical / translational (subfield)
Methods: Connectivity, Statistics, Smoothing, state filtering, decompositions, Machine learning, Preprocessing, fMRI & imaging, Physiology & signal measures
Keywords: Diseases of the nervous system, Computational biology and bioinformatics
MeSH: Brain*, Mental Disorders*, Biomarkers, Blood Glucose, Female, Glycated Hemoglobin, Humans, Male, Schizophrenia (* major topic)
Topic: Health, Environment, Cognitive Aging (Health, Toxicology and Mutagenesis, Environmental Science), according to OpenAlex
Funding: National Health and Medical Research Council (1175754, 2037887)
Citations: cited by 1 paper (Europe PMC); 57 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above.

mdibiase1/Heterogeneity-Project---GAMLSS-modeling

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: 512b7321d3cf8b86991f05148a2a75c14034dd1c, 16 June 2025
Languages: R (1)
Size: 2 files, 1 script
Software Heritage: not archived
Found in: “Code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
2 files
At the source: github.com/mdibiase1/Heterogeneity-Project---GAMLSS-modeling.git

Code availability statement

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Read it in the paper: doi.org/10.1038/s41467-026-72604-4.

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  • 1 script, each with its path and the digest of its content;
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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

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Data availability statement

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Read it in the paper: doi.org/10.1038/s41467-026-72604-4.

Versions

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 12 authors, 2 keywords, 9 MeSH terms, 1 funder, 51 references.

Cite

This paper

Di Biase, M. A., Reay, W. R., Jameei, H., Liu, Y., Tian, Y. E., Ringin, E., Rossell, S., Karantonis, J. A., Van Rheenen, T. E., Wen, J., Pantelis, C., & Zalesky, A. (2026). Biochemical and brain heterogeneity characterizes psychiatric and non-psychiatric illness. Nature communications, 17(1), 6235. https://doi.org/10.1038/s41467-026-72604-4

BibTeX

@article{dibiase2026biochemical,
author = {Di Biase, Maria A. and Reay, William R. and Jameei, Hadis and Liu, Yuanzhe and Tian, Ye E. and Ringin, Elysha and Rossell, Susan and Karantonis, James A. and Van Rheenen, Tamsyn E. and Wen, Junhao and Pantelis, Christos and Zalesky, Andrew},
title = {{Biochemical and brain heterogeneity characterizes psychiatric and non-psychiatric illness}},
journal = {Nature communications},
year = {2026},
month = may,
volume = {17},
number = {1},
pages = {6235},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-72604-4},
url = {https://doi.org/10.1038/s41467-026-72604-4},
pmid = {42103728},
pmcid = {PMC13369505}
}

RIS

TY - JOUR
AU - Di Biase, Maria A.
AU - Reay, William R.
AU - Jameei, Hadis
AU - Liu, Yuanzhe
AU - Tian, Ye E.
AU - Ringin, Elysha
AU - Rossell, Susan
AU - Karantonis, James A.
AU - Van Rheenen, Tamsyn E.
AU - Wen, Junhao
AU - Pantelis, Christos
AU - Zalesky, Andrew
TI - Biochemical and brain heterogeneity characterizes psychiatric and non-psychiatric illness
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/05/08
VL - 17
IS - 1
SP - 6235
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-72604-4
UR - https://doi.org/10.1038/s41467-026-72604-4
LA - en
ER -

CSL-JSON

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