Differential Effect of Polymorphisms on Body Mass Index Across the Life Course of Japanese: The Japan Multi-Institutional Collaborative Cohort Study

Cataloging the potential SNPs (single nucleotide polymorphisms) associated with quantitative traits, viz. BMI (body mass index), IQ (intelligence quotient) and BP (blood pressure): an updated review

Background

Single nucleotide polymorphism (SNP) variants are abundant, persistent and widely distributed across the genome and are frequently linked to the development of genetic diseases. Identifying SNPs that underpin complex diseases can aid scientists in the discovery of disease-related genes by allowing for early detection, effective medication and eventually disease prevention.

Main body

Various SNP or polymorphism-based studies were used to categorize different SNPs potentially related to three quantitative traits: body mass index (BMI), intelligence quotient (IQ) and blood pressure, and then uncovered common SNPs for these three traits. We employed SNPedia, RefSNP Report, GWAS Catalog, Gene Cards (Data Bases), PubMed and Google Scholar search engines to find relevant material on SNPs associated with three quantitative traits. As a result, we detected three common SNPs for all three quantitative traits in global populations: SNP rs6265 of the BDNF gene on chromosome 11p14.1, SNP rs131070325 of the SL39A8 gene on chromosome 4p24 and SNP rs4680 of the COMT gene on chromosome 22q11.21.

Conclusion

In our review, we focused on the prevalent SNPs and gene expression activities that influence these three quantitative traits. These SNPs have been used to detect and map complex, common illnesses in communities for homogeneity testing and pharmacogenetic studies. High blood pressure, diabetes and heart disease, as well as BMI, schizophrenia and IQ, can all be predicted using common SNPs. Finally, the results of our work can be used to find common SNPs and genes that regulate these three quantitative features across the genome.

Genetics of early growth traits

In recent years, genome-wide association studies have shed light on the genetics of early growth and its links with later-life health outcomes. Large-scale datasets and meta-analyses, combined with recently developed analytical methods, have enabled dissection of the maternal and fetal genetic contributions to variation in birth weight. Additionally, longitudinal approaches have shown differences between the genetic contributions to infant, childhood and adult adiposity. In contrast, studies of adult height loci have shown strong associations with early body length and childhood height. Early growth-associated loci provide useful tools for causal analyses: Mendelian randomization (MR) studies have provided evidence that early BMI and height are causally related to a number of adult health outcomes. We advise caution in the design and interpretation of MR studies of birth weight investigating effects of fetal growth on later-life cardiometabolic disease because birth weight is only a crude indicator of fetal growth, and the choice of genetic instrument (maternal or fetal) will greatly influence the interpretation of the results. Most genetic studies of early growth have to date centered on European-ancestry participants and outcomes measured at a single time-point, so key priorities for future studies of early growth genetics are aggregation of large samples of diverse ancestries and longitudinal studies of growth trajectories.

[Examination of Factors Affecting Life Expectancy by Prefecture Based on the Criteria of the Organisation for Economic Co-operation and Development]

OBJECTIVES

We investigated the indicators affecting life expectancy at birth and life expectancy at age 65 by multiple regression analysis and principal component analysis, and examined the factors affecting the longevity.

METHODS

We set indicators for health status, risk factors, access to care, quality of care and health care resources. Then, we conducted multiple regression analysis with life expectancy at birth and life expectancy at age 65 as the objective variables and 22 indicators as explanatory variables. Principal component analysis was also performed on the 22 indicators.

RESULTS

Men's life expectancy at birth was positively affected by hospital admission ratio and national health insurance costs, and negatively by the rate of requirement of care certification and alcohol consumption. Men's life expectancy at age 65 was positively affected by income-to-medical expenses ratio and hospitalization treatment ratio, and negatively by requiring care certification rate, smoking rate and obesity rate. Women's life expectancy at birth was positively affected by population coverage and hospitalization treatment ratio, and negatively by women's heart disease mortality rate, requiring care certification rate and smoking rate. Women's life expectancy at age 65 was positively affected by late-stage elderly medical costs and the number of doctors, and negatively by requiring care certification rate and air pollution. Principal component 1 indicated "aging high-medical-resource society", principal component 2 indicated "high mortality from heart disease", and principal component 3 indicated the "degree of risk factor".

CONCLUSIONS

On the basis of the indicators found to affect life expectancy at birth and life expectancy at age 65, it is necessary to take measures to ensure a long life.