Редактирование: WLS

Protein wntless homolog (Integral membrane protein GPR177) (Protein evenness interrupted homolog) (EVI) (Putative NF-kappa-B-activating protein 373) [C1orf139] [GPR177] [UNQ85/PRO18667]

==Publications==

{{medline-entry
|title=Evaluation of three statistical prediction models for forensic age prediction based on DNA methylation.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/29477092
|abstract=DNA methylation is a promising biomarker for forensic age prediction. A challenge that has emerged in recent studies is the fact that prediction errors become larger with increasing age due to interindividual differences in epigenetic ageing rates. This phenomenon of non-constant variance or heteroscedasticity violates an assumption of the often used method of ordinary least squares (OLS) regression. The aim of this study was to evaluate alternative statistical methods that do take heteroscedasticity into account in order to provide more accurate, age-dependent prediction intervals. A weighted least squares ([[WLS]]) regression is proposed as well as a quantile regression model. Their performances were compared against an OLS regression model based on the same dataset. Both models provided age-dependent prediction intervals which account for the increasing variance with age, but [[WLS]] regression performed better in terms of success rate in the current dataset. However, quantile regression might be a preferred method when dealing with a variance that is not only non-constant, but also not normally distributed. Ultimately the choice of which model to use should depend on the observed characteristics of the data.
|mesh-terms=* Aging
* CpG Islands
* DNA Methylation
* Epigenomics
* Forensic Genetics
* Genetic Markers
* Humans
* Models, Statistical
* Sequence Analysis, DNA
|keywords=* DNA methylation
* Forensic age prediction
* Statistical regression modelling
|full-text-url=https://sci-hub.do/10.1016/j.fsigen.2018.02.008
}}
{{medline-entry
|title=The Influence of Social Conditions Across the Life Course on the Human Gut Microbiota: A Pilot Project With the Wisconsin Longitudinal Study.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28444239
|abstract=To test the feasibility of collecting and integrating data on the gut microbiome into one of the most comprehensive longitudinal studies of aging and health, the Wisconsin Longitudinal Study ([[WLS]]). The long-term goal of this integration is to clarify the contribution of social conditions in shaping the composition of the gut microbiota late in life. Research on the microbiome, which is considered to be of parallel importance to human health as the human genome, has been hindered by human studies with nonrandomly selected samples and with limited data on social conditions over the life course. No existing population-based longitudinal study had collected fecal specimens. Consequently, we created an in-person protocol to collect stool specimens from a subgroup of [[WLS]] participants. We collected 429 stool specimens, yielding a 74% response rate and one of the largest human samples to date. The addition of data on the gut microbiome to the [[WLS]]-and to other population based longitudinal studies of aging-is feasible, under the right conditions, and can generate innovative research on the relationship between social conditions and the gut microbiome.
|mesh-terms=* Adolescent
* Adult
* Aged
* Aging
* Feces
* Female
* Gastrointestinal Microbiome
* Humans
* Longitudinal Studies
* Male
* Middle Aged
* Pilot Projects
* Research Design
* Social Conditions
* Wisconsin
* Young Adult
|keywords=* Biodemography
* Health disparities
* Survey methods
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5926979
}}
{{medline-entry
|title=Targeted sequencing of genome wide significant loci associated with bone mineral density (BMD) reveals significant novel and rare variants: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) targeted sequencing study.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/27616567
|abstract=Bone mineral density (BMD) is a heritable phenotype that predicts fracture risk. We performed fine-mapping by targeted sequencing at [[WLS]], [[MEF2C]], [[ARHGAP1]]/F2 and [[JAG1]] loci prioritized by eQTL and bioinformatic approaches among 56 BMD loci from our previous GWAS meta-analysis. Targeted sequencing was conducted in 1,291 Caucasians from the Framingham Heart Study ( n =  925) and Cardiovascular Health Study ( n =  366), including 206 women and men with extreme low femoral neck (FN) BMD. A total of 4,964 sequence variants (SNVs) were observed and 80% were rare with MAF <1%. The associations between previously identified SNPs in these loci and BMD, while nominally significant in sequenced participants, were no longer significant after multiple testing corrections. Conditional analyses did not find protein-coding variants that may be responsible for GWAS signals. On the other hand, in the sequenced subjects, we identified novel associations in [[WLS]] , [[ARHGAP1]] , and 5' of [[MEF2C]] ( P- values < 8x10  -   5 ; false discovery rate (FDR) q-values < 0.01) that were much more strongly associated with BMD compared to the GWAS SNPs. These associated SNVs are less-common; independent from previous GWAS signals in the same loci; and located in gene regulatory elements. Our findings suggest that protein-coding variants in selected GWAS loci did not contribute to GWAS signals. By performing targeted sequencing in GWAS loci, we identified less-common and rare non-coding SNVs associated with BMD independently from GWAS common SNPs, suggesting both common and less-common variants may associate with disease risks and phenotypes in the same loci.
|mesh-terms=* Aging
* Bone Density
* Cardiovascular Diseases
* Cohort Studies
* Epidemiologic Studies
* Female
* Femur Neck
* GTPase-Activating Proteins
* Genetic Predisposition to Disease
* Genome-Wide Association Study
* Humans
* MEF2 Transcription Factors
* Male
* Middle Aged
* Polymorphism, Single Nucleotide

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837042
}}