# Differences in drug intake levels (high versus low takers) do not necessarily imply distinct drug user types: Insights from a new cluster-based model

**Authors:** Diego M. Castaneda, Martin O. Job, Rita Fuchs, Rita Fuchs, Rita Fuchs

PMC · DOI: 10.1371/journal.pone.0340165 · PLOS One · 2026-02-02

## TL;DR

This study challenges the idea that high and low drug intake levels in rats represent distinct user types, showing that intake differences don't always reflect underlying behavioral differences.

## Contribution

A new cluster-based model reveals that high and low drug takers may not represent distinct phenotypes.

## Key findings

- High and low takers (HT/LT) are composed of mixed individuals from distinct behavioral clusters.
- HT and LT groups are not significantly different when considering additional behavioral variables.
- The cluster-based model identifies more distinct groups than the traditional HT/LT classification.

## Abstract

A current model categorizes drug takers into high versus low takers (HT and LT) based on their drug intake levels, with the assumption that these groups represent different phenotypes. When several drug doses are considered, the inverted u-shaped dose-response curves (IUDR) of HT are shifted upwards and rightward, relative to that of LT. However, these IUDR ‘shifts’ are not quantitative metrics and may be subjective. Also, differences in intake levels do not necessarily imply distinctions in other variables (such as demand elasticity) that are important for drug user phenotypology. With supporting evidence from a recent report, we hypothesized that, contrary to assumptions in the field, HT and LT do not necessarily represent distinct phenotypes.

Male Sprague Dawley rats (n = 12) self-administered different doses of cocaine, and we obtained IUDR and demand curves per individual. We developed a new model to quantify the variables that defined the structure of the IUDR and we employed behavioral economic principles to obtain variables that defined the demand curve. We conducted principal component analysis/gaussian mixtures model clustering of variables from both IUDR and demand curves, to identify/compare the clusters that were revealed to HT/LT groups that were distinguished via median split.

The cluster-based model identified groups more distinct than LT versus HT. LT and HT were composed of mixtures of individuals from these distinct clusters. LT/HT were not very different when several other variables were considered.

Differences in drug intake levels (HT versus LT) do not necessarily imply distinct phenotypes.

## Linked entities

- **Chemicals:** cocaine (PubChem CID 2826)

## Full-text entities

- **Genes:** Pcsk1 (proprotein convertase subtilisin/kexin type 1) [NCBI Gene 25204] {aka BDP, PC1, PC3}, Podxl (podocalyxin-like) [NCBI Gene 192181] {aka PC, PCLP-1, podocalyxin}, Rita1 (RBPJ interacting and tubulin associated 1) [NCBI Gene 288683] {aka RGD1306772, Rita}, Pcsk2 (proprotein convertase subtilisin/kexin type 2) [NCBI Gene 25121]
- **Diseases:** LT (MESH:D009800), pain (MESH:D010146), HT (MESH:D008228), Drug Abuse (MESH:D019966), HT (MESH:D006973), infection (MESH:D007239)
- **Chemicals:** Isoflurane (MESH:D007530), sucrose (MESH:D013395), enrofloxacin (MESH:D000077422), LT (-), Meloxicam (MESH:D000077239), Cocaine (MESH:D003042), heparin (MESH:D006493)
- **Species:** Homo sapiens (human, species) [taxon 9606], Rattus norvegicus (brown rat, species) [taxon 10116]
- **Mutations:** C313CAC, C with A

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12863560/full.md

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12863560/full.md

## References

118 references — full list in the complete paper: https://tomesphere.com/paper/PMC12863560/full.md

---
Source: https://tomesphere.com/paper/PMC12863560