Evidence map›Paper›PMID 34162918›Full record

Observational studyScientific reports2021

Interaction of genetic and environmental factors for body fat mass control: observational study for lifestyle modification and genotyping.

Joon Ho Kang, Heewon Kim, Jinki Kim, Jong-Hwa Seo, Soyeon Cha, Hyunjung Oh, Kyunga Kim, Seong-Jin Park, Eunbin Kim, Sunga Kong and 7 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 14% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Review
  8. Review
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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

17 authors at 4 institutions in 1 country.

Joon Ho Kang *Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do, 16419, South Korea.
Heewon Kim *Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University, Ilwon-ro 81, Gangnam-gu, Seoul, 06351, South Korea.
Jinki Kim *AI&SW Center, SAIT, SEC, 130, Samsung-ro, Yeongtong-gu, Suwon, Gyeonggi, 16678, South Korea.
Jong-Hwa SeoAI&SW Center, SAIT, SEC, 130, Samsung-ro, Yeongtong-gu, Suwon, Gyeonggi, 16678, South Korea.
Soyeon ChaSamsung Genome Institute, Samsung Medical Center, Sungkyunkwan University, Ilwon-ro 81, Gangnam-gu, Seoul, 06351, South Korea.
Hyunjung OhSamsung Genome Institute, Samsung Medical Center, Sungkyunkwan University, Ilwon-ro 81, Gangnam-gu, Seoul, 06351, South Korea.
Kyunga KimSamsung Medical Center, Gangnam-gu, Seoul, 06351, South Korea.
Seong-Jin ParkAI&SW Center, SAIT, SEC, 130, Samsung-ro, Yeongtong-gu, Suwon, Gyeonggi, 16678, South Korea.
Eunbin KimDepartment of Clinical Nutrition, School of Public Health, Dongduk Women's University, Seoul, 02748, Korea.
Sunga KongDepartment of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea.
Jae-Hak LeeSamsung Genome Institute, Samsung Medical Center, Sungkyunkwan University, Ilwon-ro 81, Gangnam-gu, Seoul, 06351, South Korea.
Joon Seol BaeSamsung Genome Institute, Samsung Medical Center, Sungkyunkwan University, Ilwon-ro 81, Gangnam-gu, Seoul, 06351, South Korea.
Hong-Hee WonSamsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University of Medicine, Seoul, 06351, South Korea.
Je-Gun JoungSamsung Medical Center, Gangnam-gu, Seoul, 06351, South Korea.
Yoon Jung YangDepartment of Foods and Nutrition, College of Natural Sciences, Dongduk Women's University, 60, Hwarang-ro 13-gil, Seongbuk-gu, Seoul, 02748, Korea. yjyang@dongduk.ac.kr.
Jinho KimSamsung Genome Institute, Samsung Medical Center, Sungkyunkwan University, Ilwon-ro 81, Gangnam-gu, Seoul, 06351, South Korea. jinho.jk.kim@samsung.com.
Woong-Yang ParkSamsung Genome Institute, Samsung Medical Center, Sungkyunkwan University, Ilwon-ro 81, Gangnam-gu, Seoul, 06351, South Korea. woongyang.park@samsung.com.
Sungkyunkwan University · KRSamsung Medical Center · KRSamsung (South Korea) · KRDongduk Women's University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies suggested that genetic, environmental factors and their interactions could affect body fat mass (BFM). However, studies describing these effects were performed at a single time point in a population. In this study, we investigated the interaction between genetic and environmental factors in affecting BFM and implicate the healthcare utilization of lifestyle modifications from a personalized and genomic perspective. We examined how nutritional intake or physical activity changes in the individuals affect BFM concerning the genetic composition. We conducted an observational study including 259 adult participants with single nucleotide polymorphism (SNP) genotyping and longitudinal lifestyle monitoring, including food consumption and physical activities, by following lifestyle modification guidance. The participants' lifelog data on exercise and diet were collected through a wearable device for 3 months. Moreover, we measured anthropometric and serologic markers to monitor their potential changes through lifestyle modification. We examined the influence of genetic composition on body fat reduction induced by lifestyle changes using genetic risk scores (GRSs) of three phenotypes: GRS-carbohydrate (GRS-C), GRS-fat (GRS-F), and GRS-exercise (GRS-E). Our results showed that lifestyle modifications affected BFM more significantly in the high GRS class compared to the low GRS class, indicating the role of genetic factors affecting the efficiency of the lifestyle modification-induced BFM changes. Interestingly, the influence of exercise modification in the low GRS class with active lifestyle change was lower than that in the high GRS class with inactive lifestyle change (P = 0.022), suggesting the implication of genetic factors for efficient body fat control.

Indexed as

Gene-Environment InteractionLife StyleAdipose TissueAdultAgedAnthropometryBody CompositionCholesterol, HDLCholesterol, LDLDiet, Carbohydrate-RestrictedDiet, Fat-RestrictedDiet RecordsEnergy IntakeExerciseExercise TherapyFemaleCholesterol, HDLCholesterol, LDLTriglycerides

Identifiers

PMID34162918
PMCPMC8222320
OpenAlexW3174804723

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.