We aimed to present the study design and baseline cross-sectional participant characteristics of biobank innovations for chronic cerebrovascular disease with Alzheimer’s disease study (BICWALZS) participants.
A total of 1,013 participants were enrolled in BICWALZS from October 2016 to December 2020. All participants underwent clinical assessments, basic blood tests, and standardized neuropsychological tests (n=1,013). We performed brain magnetic resonance imaging (MRI, n=817), brain amyloid positron emission tomography (PET, n=713), single nucleotide polymorphism microarray chip (K-Chip, n=949), locomotor activity assessment (actigraphy, n=200), and patient-derived dermal fibroblast sampling (n=175) on a subset of participants.
The mean age was 72.8 years, and 658 (65.0%) were females. Based on clinical assessments, total of 168, 534, 211, 80, and 20 had subjective cognitive decline, mild cognitive impairment (MCI), Alzheimer’s dementia, vascular dementia, and other types of dementia or not otherwise specified, respectively. Based on neuroimaging biomarkers and cognition, 199, 159, 78, and 204 were cognitively normal (CN), Alzheimer’s disease (AD)-related cognitive impairment, vascular cognitive impairment, and not otherwise specified due to mixed pathology (NOS). Each group exhibited many differences in various clinical, neuropsychological, and neuroimaging results at baseline. Baseline characteristics of BICWALZS participants in the MCI, AD, and vascular dementia groups were generally acceptable and consistent with 26 worldwide dementia cohorts and another independent AD cohort in Korea.
The BICWALZS is a prospective and longitudinal study assessing various clinical and biomarker characteristics in older adults with cognitive complaints. Details of the recruitment process, methodology, and baseline assessment results are described in this paper.
Alzheimer’s disease (AD) is the most common cause of dementia. Nevertheless, the underlying mechanisms and pathophysiology of AD are not fully understood, and there is currently no effective treatment for AD [
Recent studies have shown that cortical amyloid burden, a hallmark of AD, frequently occurs alongside chronic cerebrovascular disease (CVD), such as white matter hyperintensities (WMH), lacunar infarction, and/or microbleeds in patients with cognitive decline [
The original goal of BICWALZS was to facilitate, regulate, and ensure optimal research use of human biospecimens and data in the field of AD, chronic CVD, and mixed pathology for mild cognitive impairment (MCI) and dementia. Considering the multifactorial nature of neurodegenerative disorders and their heterogeneous clinical presentation, it is essential to assess not only clinical characteristics but also various biomarkers such as neuroimaging results, genomics data using single nucleotide polymorphism microarray chips, and actigraphy measurements [
This paper reports the study design, methodology, and baseline clinical and biomarker characteristics of BICWALZS.
BICWALZS was planned and initiated in October 2016 by the Korea Disease Control and Prevention Agency for the Korea Biobank Project which is a national innovative biobanking program to foster biomedical and healthcare R&D infrastructure. A total of five institutions participated: Ajou University Hospital, Samsung Medical Center, Inha University Hospital, Pusan National University Hospital, and Chonnam National University Hospital. The multi-site infrastructure is linked to a centralized coordinator center and database. A coordinating committee is in place to harmonize and standardize specimen handling, technical best practices, data entry, management, and ethical and legal issues. A total of 1013 participants were enrolled in the BICWALS from October 2016 to December 2020. All participants underwent clinical assessments, blood tests, and standardized neuropsychological tests (n=1,013). From the subset of the participants, we performed brain magnetic resonance imaging (MRI, n=817), brain amyloid positron emission tomography (PET, n=713), single nucleotide polymorphism microarray chip (n=949), actigraphy measurement (n=200), and patient-derived dermal fibroblast sampling (n=175). We planned to follow all participants annually with brief assessments and participants who had cortical amyloid burden, subcortical vascular pathology, apolipoprotein E4 allele, or significant cognitive decline biannually with an expanded assessment including neuropsychological tests, actigraphy measurements, and brain MRI. We first classified the participants according to their clinical diagnosis. The subjective cognitive decline (SCD) criteria included self and/or informant reports of cognitive decline but no impairment in objective cognitive tests and daily functioning. Participants with MCI were evaluated using the expanded Mayo Clinic criteria [
BICWALZS is registered in the Korean National Clinical Trial Registry CRIS (identifier: KCT0003391). Prior to beginning the study, the Institutional Review Board approved the study plan (AJIRB-BMR-SUR-16-362). Written informed consent was obtained from all participants and caregivers. The study was conducted in accordance with the International Harmonization Conference guidelines on Good Clinical Practice.
Cognitive function was evaluated using a standardized neuropsychological test, Seoul neuropsychological screening battery (SNSB) [
Participants underwent 18F-flutemetamol PET scans using a Discovery Ste/690 PET/CT scanner (GE, Milwaukee, WI, USA) with an identical protocol. 18F-flutemetamol was injected into the antecubital vein as a bolus with a mean dose of 185 MBq. After 90 min, a 20 min PET scan (4×5 min dynamic frames) was performed. 18F-flutemetamol PET scans were co-registered to individual MRI scans, which were normalized to a T1-weighted MRI template. Using transformation parameters, MRI co-registered 18F-flutemetamol PET images were normalized to the MRI template. To quantify 18F-flutemetamol retention, the standard uptake value ratio (SUVR) was obtained using the pons as a reference region. Global cortical 18F-flutemetamol retention was calculated from the volume-weighted average SUVR of bilateral ten cortical volumes of interest from the frontal, posterior cingulate, lateral temporal, parietal, and occipital lobes using the annotated anatomical labeling atlas [
MRI scan data were obtained using a 3.0T MR scanner. Structural MRI, including 3-dimension T1, T2, fluid-attenuated inversion recovery (FLAIR) imaging, was performed. All MR images were reviewed by neuroradiologists. Inevitably, MRI machines and detailed MRI parameters were slightly different between the clinical centers. These differences were thoroughly considered in the analytic process and are fully described in
To measure chronic CVD burden, WMH were evaluated using the modified criteria of Fazekas et al. [
For baseline routine laboratory tests and blood sampling for potential peripheral biomarker research, blood samples were taken after an overnight fast in the morning by venipuncture and collected in serum separating tubes and dipotassium ethylenediaminetetraacetic acid. Baseline routine blood laboratory tests included complete blood cell count, blood urea nitrates, creatinine, albumin, liver function tests, fasting serum glucose, glycated hemoglobin (HbA1c), serum lipids, total protein, folic acid, high-sensitivity C-reactive protein, fibrinogen, venereal disease research laboratory test, treponema pallidum hemagglutination, electrolyte analysis, vitamin B12 test, homocysteine, thyroid function test, and apolipoprotein E (APOE). Blood samples were stabilized and centrifuged at 3,000 rpm for 10 min at room temperature to obtain plasma and serum supernatants. To obtain samples with high purity, the plasma and serum supernatants were further centrifuged under the same conditions, collected, and immediately stored in a -80°C deep freezer. Extracted genomic DNA specimens were also stored at -80°C for future analyses.
SNP genotyping was carried out using the Korea Biobank Array (Affymetrix Axiom KORV1.1-96 Array, Thermo Fisher Scientific, Santa Clara, CA, USA) at DNA Link Inc. (Seoul, Republic of Korea) [
A subset of participants who were recruited from Ajou University Hospital were invited to wear a research-purposed accelerometer (Fitmeter; Fit. Life Inc., Suwon, Korea) on their non-dominant wrist for at least seven days while performing their usual activities at home [
To perform ex vivo research and the potential generation of induced pluripotent stem cells (iPSCs) harboring the same genetic background of participants, we cultured and established patient-derived dermal fibroblast cells. A subset of participants agreed and donated skin biopsies for patient-derived dermal fibroblast sampling. A skin biopsy was obtained within four weeks of the baseline assessment. We planned and modified our biopsy and culture protocol based on previous studies and our preliminary experiences [
Continuous variable data were reported as the mean and standard deviation (SD), and categorical data were reported as the number of participants and percentage. We used a one-way analysis of variance (ANOVA) for continuous variables and the chi-squared test for categorical variables for group comparisons. For subsequent subgroup comparisons, we applied the Tukey method. Statistical analyses were performed using R Statistical Software, version 3.5.3 (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was set at p<0.05.
As of December 2020, a total of 1,013 participants were enrolled in BICWALZS. The demographic characteristics of the participants’ group based on clinical diagnosis are described in
A total of 817 and 713 participants agreed and underwent brain MRI and amyloid PET, respectively. We first assessed MTL neurodegeneration using Schelten’s (zero to four) scale, and a score of two or higher was considered moderate or above neurodegeneration. As a result, approximately 55.9% of the total participants who underwent brain MRI exhibited moderate or above MTL neurodegeneration. In detail, about 74.2% of participants in the AD group had MTL neurodegeneration that was moderate or above. In contrast, 31.3%, 47.8%, and 91.8% of participants showed moderate or greater MTL neurodegeneration in the SCD, MCI, and VD groups, respectively (
We performed neuropsychological tests to assess the multidomain cognitive function of the study participants and compared the results of SCD, MCI, AD, and VD groups (
Using actigraphy, activity counts in 1 min epochs from the first four consecutive days of data were analyzed to assess the locomotor activity of the participants. We assessed the group differences in mean locomotor activity with skewness. Significant differences in the mean activity were noted between the MCI and VD groups (mean±SD, 5122±1433 vs. 3775±1384, respectively, p=0.02) (
For the purposes of possible ex vivo research and potential generation of iPSCs or brain organoids harboring the same genetic background of participants, we performed skin punch biopsy and retained patient-derived dermal fibroblasts. Stabilized patient-derived dermal fibroblasts exhibited a typical cylindrical morphology with good proliferative potential (
Considering the multifactorial nature of neurodegenerative disorders and their heterogeneous clinical presentations, gathering, and integration of multi-layered clinical information, biospecimens, and patient-derived characteristics are critical steps for finding new biomarkers and developing disease modeling processes. In the BICWALZS, we recruited 1,013 older adults who complained of cognitive decline and established a multi-layered dataset including demographic, peripheral bloodbased, neuropsychological, and neuroimaging variables of the study participants. In addition, we performed SNP genotyping arrays, locomotor activity assessments and established patient-derived dermal fibroblasts in a subset of participants. We hope that our integrated clinical data structure, biospecimen, genome-wide genetic information, and patient-derived cells will facilitate optimal biomedical research for neurodegenerative disorders and disease modeling processes not only in South Korea but also abroad.
Characterization of participants’ demographic, neuropsychological, and neuroimaging results compared to similarly designed dementia cohorts might help identify and consider the cohort characteristics and possible selection bias of BICWALZS. For this, we compared our participant characteristics (age, sex, education year, MMSE score, APOE e4 allele carrier, and amyloid positivity on PET) with meta-analysis results assessing 29 cohorts, including 1,897 dementia patients and 1,849 control participants [
We also compared the two most well-known AD biomarkers, the proportion of APOE e4 allele carriers and amyloid positivity on PET. In BICWALZS participants, 46.4% of AD participants and 21.2% of VD participants were APOE e4 allele carriers. Meta-analysis results showed a higher proportion of APOE e4 allele carriers in patients with AD and VD but a relatively preserved e4 allele carrier ratio between patients with AD and VD (61.1% in AD and 28.0% in VD). This allele frequency difference was consistent with previous studies that reported a relatively lower APOE e4 allele frequency in Asian populations [
Assessing locomotor activity by actigraphy in BICWALZS participants was based on our hypothesis about a possible association between rest-activity patterns, circadian phase, and neurodegeneration in older adults. Although there is controversy on the causality of circadian disruption on neurodegeneration, several previous studies, including our report, suggest a possible association between rest-activity patterns or circadian phase changes with neurodegeneration in patients with cognitive decline [
Patient-derived dermal fibroblasts are invaluable biospecimens that have great potential for ex vivo research and disease modeling using iPSCs or brain organoid generation [
In conclusion, we constructed a BICWALZS cohort including patients with SCD, MCI, AD, and VD. The baseline characteristics of the BICWALZS participants in the MCI, AD, and VD groups are generally acceptable and consistent with worldwide dementia cohorts and independent cohorts in Korea [
The online-only Data Supplement is available with this article at
Brain MRI and amyloid PET technical parameters according to clinical sites
Demographic characteristics of the study participants according to cognitive status and neuroimaging biomarkers (N=640)
Neuropsychological test results of the study participants according to cognitive status and neuroimaging biomarkers (N=640)
The datasets generated or analyzed during the study are available from the corresponding authors upon reasonable request. For access and sharing, biological resources of the BICWALZS were stored in the BICWALZS consortium biobank (
The authors have no potential conflicts of interest to disclose.
Conceptualization: Sang Joon Son, Chang Hyung Hong. Data curation: Hyun Woong Roh, Na-Rae Kim, Dong-gi Lee. Formal analysis: Hyun Woong Roh, Na-Rae Kim, Dong-gi Lee. Investigation: Hyun Woong Roh, Jae-Youn Cheong, Sang Won Seo, Seong Hye Choi, Eun-Joo Kim, Soo Hyun Cho, Byeong C. Kim, Seong Yoon Kim, Sang Joon Son, Chang Hyung Hong. Methodology: Eun Young Kim, Jaerak Chang, Sang Yoon Lee, Dukyong Yoon, Jin Wook Choi, Young-Sil An, Hee Young Kang, Hyunjung Shin, Bumhee Park. Resources: Sang Joon Son, Chang Hyung Hong. Software: Hyun Woong Roh, Na-Rae Kim, Bumhee Park. Supervision: Sang Joon Son, Chang Hyung Hong. Validation: Sang Joon Son, Chang Hyung Hong. Visualization: Hyun Woong Roh, Na-Rae Kim. Writing—original draft: Hyun Woong Roh, Na-Rae Kim. Writing—review & editing: Bumhee Park, Sang Joon Son, Chang Hyung Hong.
This study was conducted with biospecimens and data from the consortium of the Biobank Innovations for Chronic Cerebrovascular Disease with ALZheimer’s Disease Study (BICWALZS), which was funded by the Korea Disease Control and Prevention Agency for the Korea Biobank Project (#4845-303). This work was also supported and funded by the grant from National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT (NRF-2019R1A5A2026045) and the grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the Ministry of Health & Welfare, Republic of Korea (grant number: HR21C1003).
Mean locomotor activity assessed by actigraphy according to clinical diagnosis. *p<0.05 on Tukey post hoc analysis. AD, Alzheimer’s dementia; MCI, mild cognitive impairment; SCD, subjective cognitive decline; VD, vascular dementia.
Induced pluripotent stem cells generated from patient-derived dermal fibroblast of BICWALZS participants. A: Bright imaging morphology of patient-derived dermal fibroblast and reprogramming process by conventional technique using Sendai virus; scale bars indicate 200 μm. B: Bright imaging morphology of induced pluripotent stem cell colonies, six clones from two participants, scale bars indicate 200 μm. C: Representative images of SOX2 and TRA-1-60 expression (immunofluorescence) in iPSC colonies. CL, clone; DAPI, 4,6-diamidino-2-phenylindole; SOX2, SRY-box transcription factor 2; TRA-1-60, podocalyxin.
Demographic characteristics of the study participants according to clinical diagnosis (N=1,013)
Participant characteristics | SCD (N=168) | MCI (N=534) | AD (N=211) | VD (N=80) | Others (N=20) | p |
p<0.05 |
|
---|---|---|---|---|---|---|---|---|
Age, years | 70.9±7.1 | 72.6±6.9 | 74.1±7.8 | 75.1±7.0 | 68.9±8.1 | <0.001 | a, b, c, d, e | |
Female | 115 (68.5) | 356 (66.7) | 127 (60.2) | 50 (62.5) | 10 (50.0) | 0.274 | ||
Education, years | 7.7±4.0 | 8.0±4.9 | 8.5±5.0 | 6.4±4.7 | 8.8±4.6 | 0.013 | e, f | |
Hypertension | 99 (58.9) | 282 (52.8) | 122 (57.8) | 54 (67.5) | 8 (40.0) | 0.061 | ||
Diabetes | 36 (21.4) | 111 (20.8) | 57 (27.0) | 37 (46.3) | 3 (15.0) | <0.001 | ||
Dyslipidemia | 66 (39.3) | 202 (37.8) | 58 (27.5) | 29 (36.3) | 5 (25.0) | 0.042 | ||
APOE e4 carrier | 26 (15.5) | 133 (24.9) | 98 (46.5) | 17 (21.3) | 4 (20.0) | <0.001 | ||
MMSE (0–30) | 26.2±2.8 | 24.2±3.8 | 19.0±5.1 | 18.2±4.8 | 20.6±5.3 | <0.001 | a, b, c, d, e | |
S-IADL | 3.4±3.6 | 6.6±5.6 | 16.4±10.4 | 19.7±11.1 | 19.1±9.2 | <0.001 | a, b, c, d, e, f | |
SGDS-K | 4.3±4.0 | 6.6±5.0 | 5.4±4.6 | 6.9±5.1 | 9.9±4.1 | <0.001 | a, c, d | |
GDS | 2.3±0.5 | 3.0±0.7 | 4.2±0.9 | 4.3±0.9 | 4.4±1.1 | <0.001 | ||
Aβ deposition on PET | N=82 | N=400 | N=152 | N=62 | N=17 | <0.001 | ||
(N=713) | 7 (8.5) | 107 (26.8) | 129 (84.9) | 9 (14.5) | 2 (11.8) | |||
Schelten’s scale | 1.2±0.8 | 1.6±0.8 | 2.3±0.9 | 2.6±0.8 | 1.9±0.7 | <0.001 | a, b, c, d, e, f | |
WMH on MRI (N=817) | N=102 | N=441 | N=182 | N=73 | N=19 | <0.001 | ||
Minimal | 73 ±71.6 | 283 (64.2) | 94 (51.7) | 10 (13.7) | 16 (84.2) | |||
Moderate | 25 (24.5) | 139 (31.5) | 74 (40.7) | 33 (45.2) | 3 (15.8) | |||
Severe | 4 (3.9) | 19 (4.3) | 14 (7.7) | 30 (41.1) | 0 (0.0) |
Data are shown as the mean±SD or number (%).
AD; c, SDC vs. VD; d, MCI vs. AD; e, MCI vs. VD; f, AD vs. VD. SCD, subjective cognitive decline; MCI, mild cognitive impairment; AD, Alzheimer’s dementia; VD, vascular dementia; APOE, apolipoprotein E; MMSE, mini-mental state examination; S-IADL, Seoul instrumental activities of daily living; SGDS-K, Korean version of the short form of geriatric depression scale; GDS, global deterioration scale; WMH, white matter hyperintensities
analysis of variance or chi-square test;
tukey post hoc analysis. a, SCD vs. MCI; b, SCD vs.
Neuropsychological test results according to clinical diagnosis (N=1,013)
Neuropsychological test | SCD (N=168) | MCI (N=534) | AD (N=211) | VD (N=80) | Others (N=20) | p |
p<0.05 |
|
---|---|---|---|---|---|---|---|---|
Attention function | ||||||||
Digit Span Test-backward | -0.14 (1.11) | -0.51 (1.09) | -1.09 (1.29) | -1.27 (1.23) | -1.38 (1.40) | <0.001 | a, b, c, d, e | |
Language function | ||||||||
Boston naming test | 0.40 (0.85) | -0.47 (1.32) | -1.61 (1.65) | -1.60 (1.97) | -2.35 (2.18) | <0.001 | a, b, c, d, e | |
Visuospatioal function | ||||||||
RCFT-copy | -0.04 (1.07) | -0.70 (4.70) | -2.34 (2.48) | -2.50 (2.02) | -3.38 (3.07) | <0.001 | b, c, d, e | |
Memory function | ||||||||
SVLT-delayed recall | 0.21 (0.95) | -0.89 (1.08) | -1.84 (0.94) | -1.64 (0.86) | -1.88 (0.72) | <0.001 | a, b, c, d, e | |
RCFT-delayed recall | 0.13 (0.98) | -0.73 (0.96) | -1.59 (0.78) | -1.16 (0.80) | -1.12 (1.13) | <0.001 | a, b, c, d, e, f | |
Frontal/executive function | ||||||||
Stroop test-color reading | 0.09 (0.95) | -0.77 (1.28) | -1.82 (1.63) | -2.10 (1.24) | -2.74 (1.53) | <0.001 | a, b, c, d, e | |
COWAT-phonemic task | 0.06 (0.89) | -0.64 (0.92) | -1.36 (1.05) | -1.58 (0.73) | -1.56 (0.83) | <0.001 | a, b, c, d, e |
analysis of variance;
tukey post hoc analysis.
a, SCD vs. MCI; b, SCD vs. AD; c, SDC vs. VD; d, MCI vs. AD; e, MCI vs. VD; f, AD vs. VD. AD, Alzheimer’s dementia; MCI, mild cognitive impairment; SCD, subjective cognitive decline; VD, vascular dementia; RCFT, Rey complex figure test; SVLT, Seoul verbal learning test; COWAT, controlled oral word association test-phonemic task