About

Haochang Shou, Ph.D., is an Associate Professor of Biostatistics in the Department of Biostatistics and Epidemiology at the University of Pennsylvania's Perelman School of Medicine. She is affiliated with multiple centers, including the Center for Biomedical Image Computing and Analytics (CBICA), the Center for Clinical Epidemiology (CCEB), the Center for Statistics in Big Data (CSBD), and the Center for AI And Data Science For Integrated Diagnostics (AI2D). Her methodological research primarily focuses on functional data analysis with complex structures, with particular interest in developing novel statistical modeling and estimation techniques for multimodal functional and longitudinal measurements, such as neuroimaging and human activity data. Her collaborations span brain disorder studies, mental health, and biomarker evaluation for chronic kidney disease.

Research topics

• Medicine
• Psychology
• Neuroscience
• Internal medicine
• Cognitive science
• Medical physics
• Dermatology
• Pathology
• Cognitive psychology
• Biology
• Urology
• Psychiatry
• Endocrinology

Selected publications

• Age-dependent acceleration of structural brain aging in medication-free major depressive disorder linked to neuroanatomical phenotype findings from COORDINATE-MDD consortium

  medRxiv · 2026-04-08

  articleOpen access

  Background: Major depressive disorder (MDD) is associated with altered brain structure and evidence of accelerated brain aging. However, previous studies have been limited by clinical samples with mixed medication status and multiple mood states, modest sample sizes, small percentage of MDD individuals older than 65 years of age, and/or reliance on summary-level data. Methods: Harmonized T1-weighted MRI from MDD (n = 645), all medication-free and in a current depressive episode, and matched healthy controls (n = 645), segmented into 145 regional volumes, from 11 sites in COORDINATE-MDD consortium. Brain age gap (BAG) was estimated using gradient boosting regression with nested cross-validation. Group differences in BAG (and age-corrected BAG [cBAG]) were examined across age strata. Regional contributions were evaluated using Shapley Additive exPlanations. Results: MDD was associated with significantly elevated cBAG compared with healthy controls (mean difference + 2.01 years). Age-stratified analyses showed no differences before mid-30s, with progressively larger gaps thereafter, reaching +6.85 years in MDD aged 55 and older. cBAG differed across neuroanatomical phenotypes associated with differential antidepressant response, cognitive impairment, increased adverse life events, increased self-harm and suicide attempts, and a pro-atherogenic metabolic profile. Key contributing regions included lateral and medial prefrontal regions, middle temporal gyrus, putamen, supplementary motor cortex, central operculum, and cerebellum. Conclusions: Accelerated structural brain aging in MDD is age-dependent and is most pronounced in a neuroanatomical phenotype associated with worse key clinical outcomes. The findings support neuroprogression models of MDD while demonstrating that cBAG is not a uniform feature of MDD and seem to be more strongly expressed in a specifically clinically vulnerable disease phenotype.

  PublisherOA PDFDOI

• An open, fully-processed data resource for studying mood and sleep variability in the developing brain

  Aperture Neuro · 2026-01-26

  articleOpen access

  Brain development during adolescence and early adulthood coincides with shifts in emotion regulation and sleep. Despite this co-occurrence, very few existing datasets simultaneously characterize affective dynamics, sleep variation, and multimodal measures of brain development. Here, we describe the study protocol and initial release (n = 10) of an open data resource of densely sampled behavioral measures and neuroimaging in adolescents and young adults. Behavioral measures include ecological momentary assessment, actigraphy, extensive cognitive assessments, and detailed clinical phenotyping focused on emotion regulation. All participants also complete multi-echo functional MRI, compressed-sensing diffusion MRI, and advanced arterial spin-labeled MRI. All raw and processed data are openly available without a data use agreement and will be regularly updated as accrual continues. Together, this resource will accelerate research on the links between mood, sleep, and brain development.

  PublisherOA PDFDOI

• PAFIN: PennLINC AFfective INstability- fMRIPrep Derivatives

  OpenNeuro · 2026-01-01

  datasetOpen access
  PublisherDOI

• Coupled cross-sectional and longitudinal non-negative matrix factorization reveals dominant brain aging trajectories in 48,949 individuals

  Nature Communications · 2026-04-25

  articleOpen access

  Machine learning can unravel heterogeneous patterns of brain aging and neurodegeneration, but existing methods offer limited insights into disease progression due to reliance on cross-sectional data. We introduce Coupled Cross-sectional and Longitudinal Non-negative Matrix Factorization (CCL-NMF) to capture dominant brain aging patterns by simultaneously leveraging cross-sectional and longitudinal neuroimaging data. CCL-NMF allows individuals to co-express multiple patterns, capturing mixed neuropathologic processes. Applied to neuroimaging data from 48,949 individuals from the harmonized iSTAGING study, CCL-NMF identifies seven distinct, reproducible, and biologically relevant neuroanatomical patterns. Subject-specific loading coefficients quantifying the individual expression of these patterns show distinct associations with cognition, genetic, and lifestyle factors. To support broader application, a regression-based tool was developed to estimate loadings in external cohorts without rerunning the full framework. By enabling individualized estimation of distinct brain aging patterns, these findings may improve risk assessment and therapeutic evaluation in neurodegenerative diseases. Although demonstrated using structural MRI, this framework is generalizable to other imaging modalities and biomarker types.

  PublisherOA PDFDOI

• Efficacy of pink noise and earplugs for mitigating the effects of intermittent environmental noise exposure on sleep

  SLEEP · 2026-01-14 · 2 citations

  articleOpen access

  STUDY OBJECTIVES: Nighttime environmental noise (EN) exposure disturbs sleep and increases morbidity and mortality. Affordable and effective countermeasures are needed, but rigorous research is scarce. This study investigates the efficacy of pink noise (PN) and earplugs for mitigating the effects of intermittent EN on sleep. METHODS: Twenty-five healthy adults (mean ± SD age 28.5 ± 5.9 years, seven male) participated in a seven-night polysomnographic laboratory study with different noise conditions including exposure to EN (93 events; maximum sound pressure level 45 to 65 dBA), PN (40 or 50 dBA), earplugs, and their combination. In the morning, participants completed cognitive tests, cardiovascular measurements, hearing tests, and surveys. RESULTS: Compared to a noise-free control night, EN reduced N3 deep sleep (p < .0001) while PN reduced REM sleep (p < .001). Adding PN to EN worsened sleep structure, despite minor dose-dependent improvements of EN-induced sleep fragmentation and N3 sleep increases. Earplugs mitigated nearly all EN effects on sleep but started failing at the highest EN level (65 dBA). Morning cognition, cardiovascular measures, and hearing were not affected by nighttime noise, but subjective assessments of sleep, alertness and mood were significantly worse after EN and PN exposure. CONCLUSIONS: In contrast to PN, earplugs proved efficacious in mitigating the effects of EN on sleep. Considering the importance of REM sleep for memory, emotion regulation, and neurodevelopment, the negative effects of PN on REM sleep caution against the widespread and indiscriminate use of broadband noise (BN). Additional research on optimal BN color/level and long-term use is needed, especially in vulnerable populations. CLINICAL TRIAL REGISTRATION: Registered at clinicaltrials.gov under "Broadband Sound and Sleep"; https://clinicaltrials.gov/study/NCT05774977; registration # NCT05774977.

  PublisherOA PDFDOI

• PAFIN: PennLINC AFfective INstability- QSIPrep Derivatives

  OpenNeuro · 2026-01-01

  datasetOpen access
  PublisherDOI

• The efficacy of pink noise and earplugs for mitigating sleep disruption induced by different environmental noise sources

  Sleep Health · 2026-05-01

  articleOpen access

  OBJECTIVES: To investigate the efficacy of pink noise and earplugs in mitigating sleep fragmentation induced by intermittent environmental noise. METHODS: Twenty-five healthy adults (mean ± SD age 28.5 ± 5.9 years, 7 male) participated in a polysomnographic laboratory study with intermittent exposure to environmental noise (93 events; maximum sound pressure level 45 to 65 dBA), pink noise (40 or 50 dBA), foam earplugs, and their combination. RESULTS: Pink noise mitigated aircraft noise induced arousals and awakenings in a dose-response manner but was outperformed by earplugs. Awakening and arousal probability were highest for a crying baby and a fire alarm sound, followed by helicopter, low sonic boom, drone, rail, jet, and road noise. CONCLUSIONS: Earplugs emerged as a more efficacious option for mitigating environmental noise effects on sleep disruption compared to pink noise. Noise legislation relying on jet noise studies likely underestimate the effects of helicopter noise and other emerging aircraft sounds on sleep. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT05774977.

  PublisherDOI

• Daily Physical Activity in Pulmonary Arterial Hypertension

  CHEST Journal · 2026-02-01 · 1 citations

  articleOpen access
  PublisherOA PDFDOI

• PAFIN: PennLINC AFfective INstability- QSIRecon Derivatives

  OpenNeuro · 2026-01-01

  datasetOpen access
  PublisherDOI

• Mapping the spatiotemporal continuum of structural connectivity development across the human connectome in youth

  Nature Communications · 2026-05-15

  articleOpen access

  Childhood and adolescence are marked by protracted developmental remodeling of cortico-cortical structural connectivity. However, the spatiotemporal variability of white matter connectivity development across the human connectome and its relevance to cognition and psychopathology remains unclear. Using diffusion MRI data from three independent developmental cohorts spanning youth, we identified a robust divergence in structural connectivity maturation along a predefined sensorimotor-association (S-A) connectional axis during youth (http://connectcharts.cibr.ac.cn). This developmental continuum ranged from early childhood increases in sensorimotor-sensorimotor connectivity strength to late adolescent increases in association-association connectivity strength, with the transition occurring around age 15. The S-A connectional axis also captured spatial variations in the associations between structural connectivity and both higher-order cognition and general psychopathology. Moreover, group-level developmental trajectories of structural connectivity differed by cognitive and psychopathological levels, with psychopathological effects predominantly observed in association connections. These findings delineate a spatiotemporal continuum of structural connectivity development during youth, providing a normative reference for quantifying developmental variability in psychiatric disorders.

  PublisherDOI

Frequent coauthors

• Christos Davatzikos

  University of Pennsylvania

  175 shared

• Güray Erus

  158 shared

• David A. Wolk

  California University of Pennsylvania

  122 shared

• Russell T. Shinohara

  121 shared

• Aristeidis Sotiras

  114 shared

• Susan M. Resnick

  National Institute on Aging

  110 shared

• Mohamad Habes

  101 shared

• Jimit Doshi

  University of Pennsylvania

  99 shared

Education

• PhD, Biostatistics

  Johns Hopkins University

  2014

• BSc

  Peking University

  2009