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PreprintCC BY 4.0arXiv

A signal-processing cascade linking satellite heat exposure, genomic variation, and mortality risk

  • Usman Nazir
  • Sara Khalid
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Abstract

Heat-related mortality varies among individuals under similar environmental conditions, yet environmental exposure and genetic susceptibility are typically modelled separately. We propose a signal-processing cascade linking satellite-derived land-surface temperature to sequence-dependent heat-shock response and mortality risk. The framework combines distributed-lag filtering of thermal exposure, nonlinear HSF1 activation, cross-correlation with an HSF1 position-weight-matrix kernel, and Hill-model mapping of sequence-dependent binding changes to regulatory response. Applied to 52 heat-response genes and 157 naturally occurring variants, the framework identifies 21 heat-shock-element arrays across 17 genes. Variants in canonical arrays are significantly enriched for predicted binding disruption (p=3×10−4). Propagating these effects through the cascade yields a peak predicted mortality-risk multiplier of 1.68× at $40−−42\,^{\circ}\mathrm{C}$. The framework demonstrates how environmental and genomic signals can be integrated to model inter-individual variation in heat-related risk.

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Cite

BibTeXRIS
BibTeX
@misc{nazir2026signalprocessing,
  title = {{A signal-processing cascade linking satellite heat exposure, genomic variation, and mortality risk}},
  author = {Usman Nazir and Sara Khalid},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.03667},
  eprint = {2611.03667},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.03667},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - A signal-processing cascade linking satellite heat exposure, genomic variation, and mortality risk
AU  - Usman Nazir
AU  - Sara Khalid
PY  - 2026
DA  - 2026/11/01
PB  - arXiv
DO  - 10.48550/arxiv.2611.03667
UR  - https://arxiv.org/abs/2611.03667
AB  - Heat-related mortality varies among individuals under similar environmental conditions, yet environmental exposure and genetic susceptibility are typically modelled separately. We propose a signal-processing cascade linking satellite-derived land-surface temperature to sequence-dependent heat-shock response and mortality risk. The framework combines distributed-lag filtering of thermal exposure, nonlinear HSF1 activation, cross-correlation with an HSF1 position-weight-matrix kernel, and Hill-model mapping of sequence-dependent binding changes to regulatory response. Applied to 52 heat-response genes and 157 naturally occurring variants, the framework identifies 21 heat-shock-element arrays across 17 genes. Variants in canonical arrays are significantly enriched for predicted binding disruption (p=3×10^−4). Propagating these effects through the cascade yields a peak predicted mortality-risk multiplier of 1.68× at $40−−42\,^{\circ}\mathrm{C}$. The framework demonstrates how environmental and genomic signals can be integrated to model inter-individual variation in heat-related risk.
ER  -