{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T05:24:22Z","timestamp":1772342662077,"version":"3.50.1"},"reference-count":45,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T00:00:00Z","timestamp":1640736000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T00:00:00Z","timestamp":1640736000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Neuroimaging"],"published-print":{"date-parts":[[2022,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Purpose<\/jats:title>\n                    <jats:p>Apolipoprotein E4 (APOE4) is a major genetic risk factor for Alzheimer's disease. However, the effect of APOE4 status on myelin remains unclear. This study investigated the effect of APOE4 on myelin content in cognitively impaired individuals using T2* gradient echo (GRE)\u2010based myelin water fraction (MWF) imaging.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Between August 2017 and January 2019, we evaluated 39 cognitively impaired patients (median age, 75 years; male:female = 8:31; Alzheimer's disease: mild cognitive impairment = 11:28). We obtained brain MWF values from white matter hyperintensities (WMHs) and normal\u2010appearing white matter (NAWM). Linear regression analysis was performed to investigate the relationship between the APOE4 status and MWF and cognitive function and MWF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among the 39 cognitively impaired patients, nine (23.1%) were APOE4 carriers and 30 (76.9%) were noncarriers. APOE4 carriers had a lower hippocampal volume than noncarriers (\n                      <jats:italic>p<\/jats:italic>\n                      = .045), but other brain volume parameters were not differed. After age adjustment, the APOE4 status was significantly associated with reduced MWF in NAWM (\u03b2 = \u20130.310 per allele;\n                      <jats:italic>p<\/jats:italic>\n                      = .049) but not in WMH (\u03b2 = \u20130.258 per allele;\n                      <jats:italic>p<\/jats:italic>\n                      = .113). After age adjustment, MWF in NAWM was significantly associated with Mini\u2010Mental State Examination score (\u03b2 = 0.313,\n                      <jats:italic>p<\/jats:italic>\n                      = .031).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>T2* GRE\u2010based MWF imaging can reveal myelin loss, particularly in NAWM, in cognitively impaired patients among APOE4 carriers. In vivo MWF in NAWM might be a novel imaging marker of Alzheimer's disease, for clarifying the interactions between the white matter and cognitive dysfunction with respect to the APOE4 status.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jon.12960","type":"journal-article","created":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T05:05:18Z","timestamp":1640754318000},"page":"521-529","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Brain myelin water fraction is associated with APOE4 allele status in patients with cognitive impairment"],"prefix":"10.1111","volume":"32","author":[{"given":"Mina","family":"Park","sequence":"first","affiliation":[{"name":"Department of Radiology Konkuk University Medical Center, Konkuk University School of Medicine  Seoul Korea"},{"name":"Department of Radiology, Gangnam Severance Hospital Yonsei University College of Medicine  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong Pyo","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering Yonsei University  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junghyeob","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering Yonsei University  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong Hyun","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering Yonsei University  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yeonsil","family":"Moon","sequence":"additional","affiliation":[{"name":"Department of Neurology Konkuk University Medical Center, Konkuk University School of Medicine  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8925-7376","authenticated-orcid":false,"given":"Won\u2010Jin","family":"Moon","sequence":"additional","affiliation":[{"name":"Department of Radiology Konkuk University Medical Center, Konkuk University School of Medicine  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,12,29]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2013.5847"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1101\/cshperspect.a006189"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.3348\/kjr.2016.17.6.827"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.8346443"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41582-019-0228-7"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.3233\/JAD-170036"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1212\/01.wnl.0000168863.49053.4d"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2007.01.019"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2006.08.020"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.3233\/BPL-160033"},{"key":"e_1_2_6_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.27059"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.12.008"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.25849"},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2018.03.007"},{"key":"e_1_2_6_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-018-5836-x"},{"key":"e_1_2_6_17_1","doi-asserted-by":"publisher","DOI":"10.1001\/archneur.56.3.303"},{"key":"e_1_2_6_18_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.34.7.939"},{"key":"e_1_2_6_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.11.058"},{"key":"e_1_2_6_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.3513"},{"key":"e_1_2_6_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.04.023"},{"key":"e_1_2_6_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.03.081"},{"key":"e_1_2_6_23_1","unstructured":"SchmidtP.Bayesian inference for structured additive regression models for large\u2010scale problems with applications to medical imaging. 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