Evidence map›Paper›PMID 37090135›Full record

ArticleDiabetology international2023

Comparison of the loci associated with HbA1c and blood glucose levels identified by a genome-wide association study in the Japanese population.

Takuya Sakashita, Yasuyuki Nakamura, Yoichi Sutoh, Atsushi Shimizu, Tsuyoshi Hachiya, Yayoi Otsuka-Yamasaki, Naoyuki Takashima, Aya Kadota, Katsuyuki Miura, Yoshikuni Kita and 25 more

Abstract read
In one paragraph

Article in Diabetology international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

35 authors.

Takuya SakashitaDepartment of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan.ORCID 0000-0001-5778-7113
Yasuyuki NakamuraDepartment of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan.
Yoichi SutohDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan.
Atsushi ShimizuDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan.
Tsuyoshi HachiyaDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan.
Yayoi Otsuka-YamasakiDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan.
Naoyuki TakashimaDepartment of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan.
Aya KadotaDepartment of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan.
Katsuyuki MiuraDepartment of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan.
Yoshikuni KitaDepartment of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan.
Hiroaki IkezakiDepartment of Comprehensive General Internal Medicine, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582 Japan.
Jun OtonariDepartment of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582 Japan.
Keitaro TanakaDepartment of Preventive Medicine, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga, 849-8501 Japan.
Chisato ShimanoeDepartment of Pharmacy, Saga University Hospital, 5-1-1 Nabeshima, Saga, 849-8501 Japan.
Teruhide KoyamaDepartment of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo- ku, Kyoto, 602-8566 Japan.
Isao WatanabeDepartment of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo- ku, Kyoto, 602-8566 Japan.
Sadao SuzukiDepartment of Public Health, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, 467-8601 Japan.
Hiroko Nakagawa-SendaDepartment of Public Health, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, 467-8601 Japan.
Asahi HishidaDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan.
Takashi TamuraDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan.
Yasufumi KatoDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan.
Rieko OkadaDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan.
Kiyonori KurikiLaboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526 Japan.
Sakurako Katsuura-KamanoDepartment of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, 3-18-15 Kuramoto-cho, Tokushima, 770-8503 Japan.
Takeshi WatanabeDepartment of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, 3-18-15 Kuramoto-cho, Tokushima, 770-8503 Japan.
Shiroh TanoueDepartment of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544 Japan.
Chihaya KoriyamaDepartment of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544 Japan.
Isao OzeDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, 464-8681 Japan.
Yuriko N KoyanagiDivision of Cancer Information and Control, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, 464-8681 Japan.
Yohko NakamuraCancer Prevention Center, Chiba Cancer Center Research Institute, 666-2 Nitona-cho, Chuo-ku, Chiba, 260-8717 Japan.
Miho KusakabeCancer Prevention Center, Chiba Cancer Center Research Institute, 666-2 Nitona-cho, Chuo-ku, Chiba, 260-8717 Japan.
Masahiro NakatochiPublic Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya, 461-8673 Japan.
Yukihide MomozawaLaboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045 Japan.
Kenji WakaiDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan.
Keitaro MatsuoDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, 464-8681 Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Hemoglobin A1c (HbA1c) levels are widely employed to diagnose diabetes. However, estimates of the heritability of HbA1c and glucose levels are different. Therefore, we explored HbA1c- and blood glucose-associated loci in a non-diabetic Japanese population. Methods: We conducted a two-stage genome-wide association study (GWAS) on variants associated with HbA1c and blood glucose levels in a Japanese population. In the initial stage, data of 4911 participants of the Japan Multi-Institutional Collaborative Cohort (J-MICC) were subjected to discovery analysis. In the second stage, two datasets from the Tohoku Medical Megabank project, with 8175 and 40,519 participants, were used for the replication study. Association of the imputed variants with HbA1c and blood glucose levels was determined via linear regression analyses adjusted for age, sex, body mass index (BMI), smoking, and genetic principal components (PC1-PC10). Moreover, we performed a BMI-stratified GWAS on HbA1c levels in the J-MICC. The discovery analysis and BMI-stratified GWAS results were validated with re-analyses of normalized HbA1c levels adjusted for site in addition to the above, and blood glucose adjusted for fasting time as an additional covariate. Results: Genetic variants associated with HbA1c levels were identified in Conclusions: The variant rs2299620 in Supplementary Information: The online version contains supplementary material available at 10.1007/s13340-023-00618-0.

Indexed as

Blood glucoseBody mass indexDiabetesGenome-wide association studyHbA1cJapanese population

Identifiers

PMID37090135
PMCPMC10113415

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