OSCR

Early-life blood pressure and midlife brain and cognitive health: tests in two birth cohorts.

Code ↔ Paper

The paper beside its authors' code: matches between them have not been computed for this paper yet.

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

Stata · 215 lines · 7.5 KB · no license

  1. *****************************************************************************************************************************************************************
  2. **************************************************************BCS70 Blood Pressure and Cognition Analyses********************************************************
  3. **************************************************************************Mugoba et al 2026**********************************************************************
  4. *****************************************************************************************************************************************************************
  6. *****************************************************************************STATA SET-UP************************************************************************
  8. **Standard settings**
  10. version 17
  11. clear all
  12. macro drop _all
  13. set more off
  14. set maxvar 10000
  16. *********************************************************************DATASET MERGING AND PREPARATION*************************************************************
  18. cd "Y:\Dunedin Paper\Datasets"
  19. use "bcs_age46_main.dta", clear
  20. log using "Final Analysis", replace
  22. *************************EARLY-LIFE FACTORS********************************
  24. //Age and Sex//
  26. replace BD10AGEINT = . if BD10AGEINT < 0
  27. rename BD10AGEINT age
  29. replace B10CMSEX = . if B10CMSEX < 0
  30. rename B10CMSEX sex
  32. rename BCSID bcsid
  33. merge 1:1 bcsid using "bcs2000.dta", keepusing(ethnic)
  34. replace ethnic = . if ethnic > 97
  35. recode ethnic (1/3 = 0) (4/16 = 1)
  36. label define ethnic 0 "White" 1 "Non-White", modify
  37. label values ethnic ethnic
  38. rename bcsid BCSID
  39. drop if _merge == 2
  40. drop _merge
  42. //Birthweight//
  44. merge 1:1 BCSID using "bcs70_1975_developmental_history.dta", keepusing(VAR5542)
  45. drop _merge
  46. replace VAR5542 = . if VAR5542 < 0
  47. rename VAR5542 BW
  49. //Childhood Socioeconomic Status//
  51. merge 1:1 BCSID using "bcs2derived.dta", keepusing(BD2SOC)
  52. drop _merge
  54. replace BD2SOC = . if BD2SOC < 0
  55. rename BD2SOC SES
  56. drop if SES == 0
  58. //Household Overcrowding//
  60. rename BCSID bcsid
  61. merge 1:1 bcsid using "f699b.dta", keepusing(e228b)
  62. drop _merge
  63. replace e228b = . if e228b < 0
  64. rename e228b Overcrowding
  66. //Age 10 Cognition//
  68. merge 1:1 bcsid using "EarlyChildhoodCognition.dta", keepusing(harm_gc1_10 harm_gf_10 harm_gq_10 harm_gc2_10 cog_g_10) //created using do file called Preparing Childhood Cognitive Scores//
  69. drop if _merge == 2
  70. drop _merge
  71. rename bcsid BCSID
  73. //Highest Education Level//
  75. merge 1:1 BCSID using "bcs6derived.dta", keepusing(HIACA00)
  76. drop _merge
  77. replace HIACA00 = . if HIACA00 < 0
  78. rename HIACA00 Highest_Ed
  79. recode Highest_Ed (0 = 10) (1/2 = 11) (3/5 = 12) (6 = 13) (7/8 = 14)
  80. label define Highest_Ed 10 "No education" 11 "Below Ordinary Secondary Education" 12 "Ordinary Secondary Qualifications" 13 "Advanced Level Qualifications" 14 "Postgraduate or Above", modify
  81. label values Highest_Ed Highest_Ed
  84. *************************MID-LIFE FACTORS********************************
  86. //BMI//
  88. replace BD10MBMI = . if BD10MBMI < 0
  89. rename BD10MBMI Adult_BMI
  91. //Smoking//
  93. replace B10SMOKIG = . if B10SMOKIG < 0
  94. rename B10SMOKIG Smoking_Status
  96. //Malaise//
  98. replace BD10MAL = . if BD10MAL < 0
  99. rename BD10MAL Malaise
  101. //Physical Activity//
  103. merge 1:1 BCSID using "bcs_age46_activpal_avg", keepusing(B10AAMVPAH)
  104. drop _merge
  105. replace B10AAMVPAH = . if B10AAMVPAH < 0
  106. rename B10AAMVPAH Activity
  108. //Adult SES//
  110. replace B10NSSECAN = . if B10NSSECAN < 0
  111. recode B10NSSECAN (1.1 1.2 2 = 1) (3 4 = 2) (5/9 = 3)
  112. rename B10NSSECAN Adult_SES
  113. label define Adult_SES 1 "Managers" 2 "Intermediate" 3 "Lower/Technical"
  114. label values Adult_SES Adult_SES
  117. ****************************EXPOSURES***********************************
  119. //Age 10 Blood Pressure//
  121. rename BCSID bcsid
  122. merge 1:1 bcsid using "sn3723", keepusing(meb20_1 meb20_2)
  123. drop _merge
  124. replace meb20_1 = . if meb20_1 < 0
  125. replace meb20_2 = . if meb20_2 < 0
  126. rename meb20_1 Ten_Systolic
  127. rename meb20_2 Ten_Diastolic
  129. //Age 16 Blood Pressure//
  131. merge 1:1 bcsid using "bcs7016x.dta", keepusing(rd5_1 rd5_2)
  132. drop _merge
  133. replace rd5_1 = . if rd5_1 < 0
  134. replace rd5_2 = . if rd5_2 < 0
  135. rename rd5_1 Sixteen_Systolic
  136. rename rd5_2 Sixteen_Diastolic
  138. //Age 46 Blood Pressure//
  140. replace B10BPSYSR2 = . if B10BPSYSR2 < 0
  141. rename B10BPSYSR2 Second_Adult_Systolic
  142. replace B10BPSYSR3 = . if B10BPSYSR3 < 0
  143. rename B10BPSYSR3 Third_Adult_Systolic
  144. replace B10BPDIAR2 = . if B10BPDIAR2 < 0
  145. rename B10BPDIAR2 Second_Adult_Diastolic
  146. replace B10BPDIAR3 = . if B10BPDIAR3 < 0
  147. rename B10BPDIAR3 Third_Adult_Diastolic
  149. gen Adult_Systolic = (Second_Adult_Systolic + Third_Adult_Systolic)/2
  150. gen Adult_Diastolic = (Second_Adult_Diastolic + Third_Adult_Diastolic)/2
  152. ****************************OUTCOMES***********************************
  154. //Immediate and Delayed Recall//
  156. replace B10CFLISN = . if B10CFLISN < 0
  157. rename B10CFLISN Imm_Recall
  159. replace B10CFLISD = . if B10CFLISD < 0
  160. rename B10CFLISD Delay_Recall
  162. //Processing Speed//
  164. replace B10CFRC = . if B10CFRC < 0
  165. rename B10CFRC Speed_Score
  167. //Verbal Fluency//
  169. replace B10CFANI = . if B10CFANI < 0
  170. rename B10CFANI Verbal_Fluency
  172. //Overall Cognition//
  174. pca Imm_Recall Delay_Recall Verbal_Fluency Speed_Score
  175. predict final_cog, score
  176. drop if final_cog ==.
  178. //Z-Score Variables of Interest//
  180. zscore Ten_Systolic Ten_Diastolic Sixteen_Systolic Sixteen_Diastolic Adult_Systolic Adult_Diastolic Imm_Recall Delay_Recall Speed_Score Verbal_Fluency
  182. save "cleaned dataset.dta", replace
  185. ***********************************************************************DESCRIPTIVES****************************************************************
  187. use "cleaned dataset.dta", clear
  189. sum age BW Overcrowding cog_g_10 Adult_BMI Malaise Activity Ten_Systolic Ten_Diastolic Sixteen_Systolic Sixteen_Diastolic Adult_Systolic Adult_Diastolic final_cog Imm_Recall Delay_Recall Verbal_Fluency Speed_Score tab1 sex SES Highest_Ed Smoking_Status Adult_SES
  192. *************************************************************************IMPUTE********************************************************************
  194. mi set wide
  195. mi register regular age sex z_Imm_Recall z_Delay_Recall z_Speed_Score z_Verbal_Fluency final_cog Smoking_Status
  196. mi register imputed z_Ten_Systolic z_Ten_Diastolic z_Sixteen_Systolic z_Sixteen_Diastolic z_Adult_Systolic z_Adult_Diastolic ethnic BW SES Overcrowding cog_g_10 Highest_Ed Activity Adult_SES Malaise Adult_BMI
  197. mi impute chained (regress) z_Ten_Systolic z_Ten_Diastolic z_Sixteen_Systolic z_Sixteen_Diastolic z_Adult_Systolic z_Adult_Diastolic BW cog_g_10 Overcrowding Activity Malaise Adult_BMI (logit) ethnic (ologit) Adult_SES SES Highest_Ed = age sex z_Imm_Recall z_Delay_Recall z_Speed_Score z_Verbal_Fluency final_cog Smoking_Status, add(50) rseed(54321) dots
  199. **********************************************************************PERFORM ANALYSES*************************************************************
  202. vl create exposures = (z_Ten_Systolic z_Ten_Diastolic z_Sixteen_Systolic z_Sixteen_Diastolic z_Adult_Systolic z_Adult_Diastolic)
  203. vl create outcomes = (final_cog z_Imm_Recall z_Delay_Recall z_Verbal_Fluency z_Speed_Score)
  205. foreach outcome of varlist $outcomes {
  206. foreach exposure of varlist $exposures {
  207. mi estimate: regress `outcome' `exposure' age i.sex i.ethnic
  208. mi estimate: regress `outcome' `exposure' age i.sex i.ethnic cog_g_10 i.SES Overcrowding
  209. mi estimate: regress `outcome' `exposure' age i.sex i.ethnic cog_g_10 SES Overcrowding i.Highest_Ed Adult_BMI i.Smoking_Status i.Adult_SES Activity Malaise
  210. }
  212. }
  214. log close

BCS70 Cognitive Analyses.do at commit 7c73e0c, no license · at the source

Overview

Authors: Mayibongwe Mugoba1, Renate M Houts2, Annchen R Knodt2, Reremoana F Theodore3, Richie Poulton3, Ahmad R Hariri2, Avshalom Caspi2,4, Terrie E Moffitt2,4, Scott T Chiesa1
ORCID iDs: Mayibongwe Mugoba, Avshalom Caspi, Scott T Chiesa
  1. Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London WC1E 7HB, UK
  2. Departments of Psychology and Neuroscience, and Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27708, USA
  3. Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin 9016, New Zealand
  4. MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychology, Psychiatry, and Neuroscience, King’s College London, London SE5 8AF, UK
Institutions: University College London (United Kingdom); Duke University (United States); University of Otago (New Zealand); King's College London (United Kingdom)
Journal: Brain communications, volume 8, issue 3, article fcag172
Dates: received 16 September 2025; accepted 12 May 2026; published online 13 May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1093/braincomms/fcag172 · PMID 42221574 · PMCID PMC13218384 · OpenAlex W7161036702
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), developmental (subfield)
Methods: Statistics, Machine learning, Preprocessing
Keywords: blood pressure, brain health, cognition, Dunedin, BCS70
Topic: Dementia and Cognitive Impairment Research (Psychiatry and Mental health, Medicine), according to OpenAlex
Funding: Alzheimer’s Research UK (ARUK-RF2021B-006); British Heart Foundation Centre of Research Excellence Springboard (CRE-SF-2025-002); National Institute for Health Research (NIHR); UCLH Biomedical Research Centre Excellence (BRC1301/CV/SG/101320); Dunedin Multidisciplinary Health and Development Research Unit; Health Research Council of New Zealand (16-604, 24/690); Ministry for Business Innovation and Employment (MBIE); National Institute on Ageing (US-NIA R01AG032282, US-NIA R01AG049789); Medical Research Council (MR/X021149/1)
Citations: not cited yet (Europe PMC); 40 references in the paper

Abstract

Elevated blood pressure (BP) in midlife is a well-established risk factor for impaired brain health and cognitive ability in old age. We hypothesized that exposure to elevated BP within the first five decades of life may contribute to this risk through impacts on brain health and/or cognitive ability evident by midlife. Participants (n = 893) were selected from the Dunedin Multidisciplinary Health and Development Study (The Dunedin Study). Exposures were systolic (SBP) and diastolic (DBP) blood pressures measured at ages 7, 11, 18, 26, 32, 38 and 45. Cumulative early-life exposure to blood pressure was also quantified as the area under the curve (AUC). Brain health was assessed at age 45 via imaging measures comprising BrainAGE (difference between chronological age and age predicted from machine-learning models of brain-imaging data), white matter hyperintensity (WMH) burden, and retinal arteriolar calibres (RAC)—a proxy for cerebral small vessel remodelling. Cognitive ability (assessed using IQ) was also measured at age 45, with replication of cognitive findings tested in a larger contemporary cohort, the 1970 British Cohort Study. We found limited evidence for any association between BP in the first four decades of life and brain health or cognitive ability at age 45. Most associations instead emerged for BP from early-midlife onwards. Midlife BP was associated with older BrainAGE (Beta for DBP at age 45 = 0.11 [0.04, 0.19]; P = 0.003) and higher WMH burden (Beta = 0.09 [0.02, 0.17]; P = 0.019). Effect estimates for SBP were similar. For cognitive ability, DBP at ages 38 and 45 showed modest associations with age 45 IQ, which became null after accounting for childhood IQ. These findings were broadly replicated in the 1970 British Cohort Study for age 47 IQ. Only RAC in The Dunedin Study were found to associate with BP from childhood (Beta for age 7 DBP = −0.09 [−0.16, −0.03]; P = 0.006), and the magnitude of these estimates increased during midlife (Beta at age 45 = −0.37 [−0.45, −0.30]; P < 0.001). We found little evidence for any association between BP prior to age 40 and BrainAGE, WMH volume, or cognitive ability in midlife. However, cumulative exposure to elevated BP from childhood was associated with reduced RAC, suggesting a potential link between BP and adverse cerebral small vessel remodelling from childhood.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

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

scottchiesa/early-life-bp-cog-brain

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: 7c73e0cdcf92bfddd937ae971a067debf66fd748, 20 April 2026
Languages: Stata (1), SAS (1)
Size: 3 files, 2 scripts
Software Heritage: not archived
Found in: “Data 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
3 files
At the source: github.com/scottchiesa/early-life-bp-cog-brain

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 2 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

Details on accessing data from The Dunedin Study can be found in the Policy Statement and Code of Practice document available at https://dunedinstudy.otago.ac.nz/. 1970 British Cohort Study data are available from the UK Data Service repository at https://ukdataservice.ac.uk. All statistical code related to this paper is available in an open-access GitHub repository located at https://github.com/scottchiesa/early-life-bp-cog-brain.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 5 keywords, 9 funders, 40 references.

Cite

This paper

Mugoba, M., Houts, R. M., Knodt, A. R., Theodore, R. F., Poulton, R., Hariri, A. R., Caspi, A., Moffitt, T. E., & Chiesa, S. T. (2026). Early-life blood pressure and midlife brain and cognitive health: tests in two birth cohorts. Brain communications, 8(3), fcag172. https://doi.org/10.1093/braincomms/fcag172

BibTeX

@article{mugoba2026early,
author = {Mugoba, Mayibongwe and Houts, Renate M and Knodt, Annchen R and Theodore, Reremoana F and Poulton, Richie and Hariri, Ahmad R and Caspi, Avshalom and Moffitt, Terrie E and Chiesa, Scott T},
title = {{Early-life blood pressure and midlife brain and cognitive health: tests in two birth cohorts}},
journal = {Brain communications},
year = {2026},
month = may,
volume = {8},
number = {3},
pages = {fcag172},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/braincomms/fcag172},
url = {https://doi.org/10.1093/braincomms/fcag172},
pmid = {42221574},
pmcid = {PMC13218384}
}

RIS

TY - JOUR
AU - Mugoba, Mayibongwe
AU - Houts, Renate M
AU - Knodt, Annchen R
AU - Theodore, Reremoana F
AU - Poulton, Richie
AU - Hariri, Ahmad R
AU - Caspi, Avshalom
AU - Moffitt, Terrie E
AU - Chiesa, Scott T
TI - Early-life blood pressure and midlife brain and cognitive health: tests in two birth cohorts
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/05/13
VL - 8
IS - 3
SP - fcag172
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/braincomms/fcag172
UR - https://doi.org/10.1093/braincomms/fcag172
LA - en
ER -

CSL-JSON

{
"id": "10.1093/braincomms/fcag172",
"type": "article-journal",
"title": "Early-life blood pressure and midlife brain and cognitive health: tests in two birth cohorts",
"container-title": "Brain communications",
"author": [
{
"family": "Mugoba",
"given": "Mayibongwe"
},
{
"family": "Houts",
"given": "Renate M"
},
{
"family": "Knodt",
"given": "Annchen R"
},
{
"family": "Theodore",
"given": "Reremoana F"
},
{
"family": "Poulton",
"given": "Richie"
},
{
"family": "Hariri",
"given": "Ahmad R"
},
{
"family": "Caspi",
"given": "Avshalom"
},
{
"family": "Moffitt",
"given": "Terrie E"
},
{
"family": "Chiesa",
"given": "Scott T"
}
],
"container-title-short": "Brain Commun",
"volume": "8",
"issue": "3",
"page": "fcag172",
"DOI": "10.1093/braincomms/fcag172",
"PMID": "42221574",
"PMCID": "PMC13218384",
"ISSN": "2632-1297",
"publisher": "Oxford University Press",
"URL": "https://doi.org/10.1093/braincomms/fcag172",
"language": "en",
"issued": {
"date-parts": [
[
2026,
5,
13
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.3390/ijms27114756
Multi-Omics Integration and Causal Inference Identify HSD17B1 as a Potential Nobiletin Target Linking Neurosteroid Metabolism to Alzheimer's Disease.
Journal: International journal of molecular sciences
In common: 4 references
[2] doi:10.1002/14651858.cd016297
Amyloid-beta-targeting monoclonal antibodies for people with mild cognitive impairment or mild dementia due to Alzheimer's disease.
Journal: The Cochrane database of systematic reviews
In common: 4 references
[3] doi:10.1186/s13195-026-02074-9
Metabolic parameter variability, brain structure, perfusion, and cognition: a population-based study.
Journal: Alzheimer's research & therapy
In common: 3 references
[4] doi:10.1002/alz.71711 [code]
Exploring longitudinal relationships among Alzheimer's disease biomarkers.
Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association
In common: 3 references
[5] doi:10.1002/hbm.70508 [code]
Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET.
Journal: Human brain mapping
In common: 3 references
[6] doi:10.3389/fnut.2026.1837406 [code]
MIND diet moderates the associations between cerebrovascular and neurodegenerative disease burden and cognition.
Journal: Frontiers in nutrition
In common: 3 references
[7] doi:10.1002/hbm.70627 [code]
Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.
Journal: Human brain mapping
In common: 2 references
[8] doi:10.64898/2026.05.06.26352540 [code]
Generating synthetic tau-PET scans in Alzheimer’s disease from MRI, blood biomarkers and demographics with deep learning
Journal: medRxiv (preprint)
In common: 2 references
[9] doi:10.3389/fnagi.2026.1931183 [code]
A validated workflow for paired total and small RNA sequencing from low-input submandibular gland biopsy specimens in &lt;i&gt;de novo&lt;/i&gt; Parkinson's disease patients.
Journal: Frontiers in aging neuroscience
In common: 2 references
[10] doi:10.1016/j.isci.2026.117250
Comparative effectiveness of multiple interventions for Alzheimer's disease on ABC syndromes and QoL: A Bayesian network meta-analysis.
Journal: iScience
In common: 2 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.