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The role of ucOCN in aerobic exercise induced amelioration of autism spectrum disorder phenotypes.

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  1. [1] § STAR★Methods › Method details › Mendelian randomization analysis ↔ Figure1.R, lines 1–38 · score 0.59 · sample MR, OpenGWAS, kb, r2, instrumental, IEU

Paper

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The authors' code

R · 171 lines · 5.4 KB · CC-BY-4.0 · 1 match

  1. #TSMR·ÖÎö
  3. #¶ÔÓÚ±©Â¶ºÍ½á¾ÖµÄÊý¾Ý¶¼À´×ÔOpen GWAS,¼´´æÔÚ±©Â¶IDºÅ
  4. #ÒÔBMIºÍCHDΪÀý£ºBMIµÄID£ºieu-a-2 CHDµÄID£ºieu-a-7
  5. #Ê×ÏÈÔÚRÀïÃæ°²×°TSMR°ü
  6. install.packages("devtools")
  7. devtools::install_github("MRCIEU/TwoSampleMR")
  9. install.packages("TwoSampleMR", repos = c("https://mrcieu.r-universe.dev", "https://cloud.r-project.org"))
  11. install.packages("ieugwasr")
  13. #ÔËÐÐTSMR
  15. library(TwoSampleMR)
  16. library(ieugwasr)
  17. Sys.setenv(OPENGWAS_JWT="eyJhbGciOiJSUzI1NiIsImtpZCI6ImFwaS1qd3QiLCJ0eXAiOiJKV1QifQ.eyJpc3MiOiJhcGkub3Blbmd3YXMuaW8iLCJhdWQiOiJhcGkub3Blbmd3YXMuaW8iLCJzdWIiOiIyMDIyMDIwMjQ1QGhyYm11LmVkdS5jbiIsImlhdCI6MTcyMTA1MTIxNiwiZXhwIjoxNzIyMjYwODE2fQ.cchJWtPtq5cSzQqCwBIaQpJF65HqZ9Ro88i7CZ8C4xg3FbTacwPWzFM291IjtR8d7w44ihMWC6TZZakLdHLhk3c_a4xBdi72E_sQyqX2QLejY3KH8rZ5pgWOr_OtdtkNMZvwtqk7WlcX3bxOhFriif7F9ImVjDU5Lu5KQa68iB3hRhaaF0wSDVWkow4lnFNSdN8-Aq2xcBt0Ex8BiKMFVKZS-9ceodsdTbxDMyumXlUZvKwLeSygGk5Z2N7wMpZ1A26z3z9SgnhVrOGptzXDPbj0BwlyLSOOqEIxTZY6N2kt4iEvPqsgLoBKHnmf19jd22YAlnej5m_bY_nO8RsPnA") #Õâ¸ötoken¾ÍÊDZ£´æÏÂÀ´Ò»³¤´®µÄÖµ£¬¸´ÖƽøÈ¥¾Í¿ÉÒÔÁË
  19. exp<-extract_instruments(outcomes= c("ebi-a-GCST90019418"),p1 = 5e-08)
  20. #ÌáÈ¡±©Â¶BMIµÄ¹¤¾ß±äÁ¿
  21. bmi_exp_dat <- extract_instruments(outcomes = 'ebi-a-GCST90019418')
  23. #½âÊÍextract_instrumentsº¯Êý
  24. #extract_instruments(outcomes,p1 = 5e-08,clump = TRUE,
  25. #p2 = 5e-08,r2 = 0.001,kb = 10000,access_token = ieugwasr::check_access_token(),
  26. #force_server = FALSE)
  28. #Èç¹ûÏëÒªµ÷Õûclump²ÎÊý
  29. bmi <- extract_instruments(outcomes = 'ieu-a-2',
  30. clump = TRUE, r2 = 0.01,
  31. kb = 5000, access_token = NULL)
  33. #Èç¹ûÏëÒªµ÷ÕûPÖµ
  34. bmi_1 <- extract_instruments(outcomes = 'ebi-a-GCST90019418',
  35. p1 = 5e-06,
  36. clump = TRUE,
  37. r2 = 0.001,
  38. kb = 10000)
  41. #ÌáÈ¡¹¤¾ß±äÁ¿ÔÚ½á¾ÖÖеÄÐÅÏ¢
  42. chd_out_dat <- extract_outcome_data(snps = bmi_exp_dat$SNP, outcomes = 'ieu-a-1185')
  44. #½«±©Â¶ºÍ½á¾ÖµÄÊý¾Ý½øÐкϲ¢£¬²úÉúÓÃÓÚ½øÐÐMR·ÖÎöµÄÊý¾Ý
  45. #µÚÒ»ÖÖ´úÂ룺
  46. dat <- harmonise_data(bmi_exp_dat, chd_out_dat)
  47. #µÚ¶þÖÖ´úÂ룺
  48. dat <- harmonise_data(
  49. exposure_dat=bmi_exp_dat,
  50. outcome_dat=chd_out_dat,
  51. action= 2
  52. )
  54. #MR·ÖÎöµÄÖ÷Òª½á¹û:ĬÈÏÓÃ5ÖÖ·½·¨½øÐÐMR·ÖÎö
  55. res <- mr(dat)
  56. res
  58. #»»Ëã³ÉORÖµ
  59. OR <-generate_odds_ratios(res)
  60. OR
  62. #Èç¹ûMR·ÖÎöÖÐÏÞ¶¨·½·¨£¬ÈçÖ»ÓÃmr_eggerºÍmr_ivw
  63. mr(dat, method_list = c("mr_egger_regression", "mr_ivw"))
  65. #ʹÓÃËæ»úЧӦģÐÍ
  66. RE <-mr(dat,method_list=c('mr_ivw_mre'))
  67. REOR <-generate_odds_ratios(RE)
  69. #¹Ì¶¨Ð§Ó¦Ä£ÐÍ
  70. FE <-mr(dat,method_list=c('mr_ivw_fe'))
  71. FEOR <-generate_odds_ratios(FE)
  73. #ÀëȺֵ¼ìÑé
  74. #°²×°MRPRESSO°ü
  75. devtools::install_github("rondolab/MR-PRESSO",force = TRUE)
  77. #°²×°ÍêÔËÐÐ
  78. library(MRPRESSO)
  79. mr_presso(BetaOutcome ="beta.outcome", BetaExposure = "beta.exposure", SdOutcome ="se.outcome", SdExposure = "se.exposure",
  80. OUTLIERtest = TRUE,DISTORTIONtest = TRUE, data = dat, NbDistribution = 1000,
  81. SignifThreshold = 0.05)
  83. #µ¥¸ösnp·ÖÎö-£¨ÈýÖÖ·½·¨£©
  84. #ĬÈÏWald±ÈÖµ
  85. res_single <- mr_singlesnp(dat)
  86. ORR <-generate_odds_ratios(res_single)
  88. #Êý¾ÝÃô¸ÐÐÔ·ÖÎö
  89. #ÒìÖÊÐÔ¼ìÑé
  90. het <- mr_heterogeneity(dat)
  91. het
  92. #¶àЧÐÔ¼ìÑé
  93. pleio <- mr_pleiotropy_test(dat)
  94. pleio
  95. #Öð¸öÌÞ³ý¼ìÑé
  96. single <- mr_leaveoneout(dat)
  97. mr_leaveoneout_plot(single)
  98. #É¢µãͼ
  99. mr_scatter_plot(res,dat)
  100. #É­ÁÖͼ
  101. res_single <- mr_singlesnp(dat)
  102. mr_forest_plot(res_single)
  103. #©¶·Í¼
  104. mr_funnel_plot(res_single)
  107. #±£´æÊý¾Ý
  108. #°²×°xlsx
  109. install.packages('xlsx')
  110. #ÔËÐÐxlsx
  111. library(xlsx)
  112. write.xlsx(ORR, "D:xx.xls")
  114. #±¾µØΪ±©Â¶Îļþ£¬½á¾ÖΪ CHDµÄID£ºieu-a-7
  115. #ÔËÐÐTSMR
  116. library(TwoSampleMR)
  117. #¶ÁÈ¡±©Â¶±¾µØÊý¾Ý
  118. exp_dat <- read_exposure_data(
  119. filename = 'Blood selenium.csv',
  120. sep= ",",
  121. snp_col = "SNP",
  122. beta_col = "Beta",
  123. se_col = "SE",
  124. effect_allele_col ="EA",
  125. other_allele_col = "NEA",
  126. eaf_col = "EAF",
  127. pval_col = "P"
  128. )
  129. exp_dat$exposure <- "Blood selenium"
  130. #¶ÁÈ¡¹¤¾ß±äÁ¿ÔÚ½á¾Öµ±ÖеÄÐÅÏ¢
  131. CHD_out <- extract_outcome_data(
  132. snps=exp_dat$SNP,
  133. outcomes='ieu-a-7',
  134. proxies = FALSE,
  135. maf_threshold = 0.01,
  136. access_token = NULL
  137. )
  138. mydata <- harmonise_data(
  139. exposure_dat=exp_dat,
  140. outcome_dat=CHD_out,
  141. action= 2
  142. )
  143. res <- mr(mydata)
  144. res
  145. OR <-generate_odds_ratios(res)
  146. OR
  147. #ÒìÖÊÐÔ
  148. het <- mr_heterogeneity(mydata)
  149. het
  150. #¶àЧÐÔ
  151. pleio <- mr_pleiotropy_test(mydata)
  152. pleio
  153. #Öð¸öÌÞ³ý¼ìÑé
  154. single <- mr_leaveoneout(mydata)
  155. mr_leaveoneout_plot(single)
  156. #É¢µãͼ
  157. mr_scatter_plot(res,mydata)
  158. #É­ÁÖͼ
  159. res_single <- mr_singlesnp(mydata)
  160. mr_forest_plot(res_single)
  161. #©¶·Í¼
  162. mr_funnel_plot(res_single)
  164. #½á¾ÖΪ±¾µØÎļþ£¬Ôõô¶ÁÈ¡
  165. #Å®ÐÔÉöϸ°û°©GWASÊý¾Ý¶ÁÈ¡
  166. library(data.table)
  167. t2d <-fread('RCC_Females.txt',header=T)
  168. #¿´Êý¾ÝÇ°ÁùÁÐ
  169. head(t2d)
  171. #µ±½«½á¾Ö±äÁ¿×ª»»³ÉÎÒÃÇ¿ÉÒÔʹÓõÄTSMRÖнá¾ÖµÄÐÎʽ£¬Ó¦Óú¯Êýformat_data

Figure1.R, under CC-BY-4.0 · at the source

Overview

Authors: Yaxin Shi1, Tikang Zhu1, Shuting Wang1, Yao Sun1, Yutong Liu1, Shuangshuang Chen1, Wanying Qiao1, Ding Zhou1, Zuyue Wang1, Lili Fan2, Hongmei Wu3
  1. Department of Children’s and Adolescent Health, Public Health College, Harbin Medical University, Harbin 150081, China
  2. Department of Children’s and Adolescent Health, Public Health College, Harbin Medical University, Harbin150081, China; Key Laboratory of Children Development and Genetic Research, Heilongjiang Province, Harbin Medical University, Harbin 150081, China
  3. Department of Psychology, College of Nursing, Harbin Medical University in Daqing, Key Laboratory of Basic Research and Health Management on Chronic Diseases in Heilongjiang Province, Daqing, Heilongjiang 163319, China
Institutions: Harbin Medical University (China)
Journal: iScience, volume 29, issue 7, article 116541
Dates: received 30 October 2025; accepted 9 June 2026; published online 29 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1016/j.isci.2026.116541 · PMID 42491620 · PMCID PMC13378376 · OpenAlex W7166585099
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: autism (population), cellular / molecular (subfield)
Methods: Spectral & time-frequency, Statistics
Keywords: molecular biology, neuroscience, behavioral neuroscience
Topic: Autism Spectrum Disorder Research (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Citations: not cited yet (Europe PMC); 63 references in the paper
Research resources: RRID:AB_2315112, Synapsin I (SYN1) antibody RRID:AB_2800493, PSD95 antibody RRID:AB_2827690, Akt2 antibody RRID:AB_2881064, p44/42 MAPK (Erk1/2) antibody RRID:AB_390779

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, with 1 match between paragraphs and lines of code.

Zenodo 20341874

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Code”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: data.table (2 files), DESeq2 (1 file), tidyverse (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
2 files
At the source: doi.org/10.5281/zenodo.20341874

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

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What the map holds:

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  • 2 scripts, each with its path and the digest of its content;
  • 1 match between paragraphs of the paper and lines of the code (method lexical-v1);
  • 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

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Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1016/j.isci.2026.116541.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 11 authors, 3 keywords, 63 references, 5 RRIDs.

Cite

This paper

Shi, Y., Zhu, T., Wang, S., Sun, Y., Liu, Y., Chen, S., Qiao, W., Zhou, D., Wang, Z., Fan, L., & Wu, H. (2026). The role of ucOCN in aerobic exercise induced amelioration of autism spectrum disorder phenotypes. iScience, 29(7), 116541. https://doi.org/10.1016/j.isci.2026.116541

BibTeX

@article{shi2026role,
author = {Shi, Yaxin and Zhu, Tikang and Wang, Shuting and Sun, Yao and Liu, Yutong and Chen, Shuangshuang and Qiao, Wanying and Zhou, Ding and Wang, Zuyue and Fan, Lili and Wu, Hongmei},
title = {{The role of ucOCN in aerobic exercise induced amelioration of autism spectrum disorder phenotypes}},
journal = {iScience},
year = {2026},
month = jun,
volume = {29},
number = {7},
pages = {116541},
publisher = {Elsevier},
issn = {2589-0042},
doi = {10.1016/j.isci.2026.116541},
url = {https://doi.org/10.1016/j.isci.2026.116541},
pmid = {42491620},
pmcid = {PMC13378376}
}

RIS

TY - JOUR
AU - Shi, Yaxin
AU - Zhu, Tikang
AU - Wang, Shuting
AU - Sun, Yao
AU - Liu, Yutong
AU - Chen, Shuangshuang
AU - Qiao, Wanying
AU - Zhou, Ding
AU - Wang, Zuyue
AU - Fan, Lili
AU - Wu, Hongmei
TI - The role of ucOCN in aerobic exercise induced amelioration of autism spectrum disorder phenotypes
T2 - iScience
J2 - iScience
PY - 2026
DA - 2026/06/29
VL - 29
IS - 7
SP - 116541
SN - 2589-0042
PB - Elsevier
DO - 10.1016/j.isci.2026.116541
UR - https://doi.org/10.1016/j.isci.2026.116541
LA - en
ER -

CSL-JSON

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{
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{
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"PMCID": "PMC13378376",
"ISSN": "2589-0042",
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