scholarly journals Rare and low-frequency coding variants alter human adult height

Nature ◽  
2017 ◽  
Vol 542 (7640) ◽  
pp. 186-190 ◽  
Author(s):  
Eirini Marouli ◽  
◽  
Mariaelisa Graff ◽  
Carolina Medina-Gomez ◽  
Ken Sin Lo ◽  
...  
Author(s):  
Darlène Antoine ◽  
Rosa-Maria Guéant-Rodriguez ◽  
Jean-Claude Chèvre ◽  
Sébastien Hergalant ◽  
Tanmay Sharma ◽  
...  

Abstract Context A recent study identified 14 low-frequency coding variants associated with body-mass-index (BMI) in 718,734 individuals predominantly of European ancestry. Objective and design The 14 low-frequency coding variants were genotyped or sequenced in 342 French adults with severe/morbid obesity and 574 French adult controls from the general population. We built risk and protective genetic scores (GS) based on 6 BMI-increasing and 5 BMI-decreasing low-frequency coding variants that were polymorphic in our study. We investigated the association of the two GS with i) the risk of severe/morbid obesity, ii) BMI variation before weight-loss intervention, iii) BMI change in response to an 18-month lifestyle/behavioral intervention program, and iv) BMI change up to 24 months after bariatric surgery. Results While the risk GS was not associated with severe/morbid obesity status, BMI-decreasing low-frequency coding variants were significantly less frequent in patients with severe/morbid obesity than in French adults from the general population. Neither the risk nor the protective GS was associated with BMI before intervention in patients with severe/morbid obesity, nor did they impact BMI change in response to a lifestyle/behavioral modification program. The protective GS was associated with a greater BMI decrease following bariatric surgery. The risk and protective GS were associated with a higher and lower risk of BMI regain after bariatric surgery. Conclusion Our data indicate that in populations of European descent, low-frequency coding variants associated with BMI in the general population also impact the outcomes of bariatric surgery in patients with severe/morbid obesity.


PLoS ONE ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. e0193547 ◽  
Author(s):  
Xiang Jiao ◽  
Wen Liu ◽  
Hovsep Mahdessian ◽  
Patrick Bryant ◽  
Jenny Ringdahl ◽  
...  

2017 ◽  
Vol 173 (6) ◽  
pp. 1531-1538 ◽  
Author(s):  
Elizabeth J. Leslie ◽  
Jenna C. Carlson ◽  
John R. Shaffer ◽  
Carmen J. Buxó ◽  
Eduardo E. Castilla ◽  
...  

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Jason Flannick ◽  
Christian Fuchsberger ◽  
Anubha Mahajan ◽  
Tanya M. Teslovich ◽  
Vineeta Agarwala ◽  
...  

Abstract To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1–5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.


2020 ◽  
Author(s):  
Dongjing Liu ◽  
Nora Alhazmi ◽  
Harold Matthews ◽  
Myoung Keun Lee ◽  
Jiarui Li ◽  
...  

AbstractThe contribution of low-frequency variants to the genetic architecture of normal-range facial traits is unknown. We studied the influence of low-frequency coding variants (MAF < 1%) on multi-dimensional facial shape phenotypes in 2329 healthy Europeans. We used MultiSKAT o scan the exome for face-associated low-frequency variants in a gene-based manner. Seven genes (AR, CARS2, FTSJ1, HFE, LTB4R, TELO2, NECTIN1) were significantly associated with shape variation of the cheek, chin, nose and mouth areas. These genes displayed a wide range of phenotypic effects, with some impacting the full face and others affecting localized regions. The missense variant rs142863092 in NECTIN1 had a significant effect on chin morphology, and was predicted bioinformatically to be deleterious. NECTIN1 is an established craniofacial gene that underlies a human syndrome that includes a mandibular phenotype. We further showed that nectin1a mutations can affect zebrafish craniofacial development, with the size and shape of the mandibular cartilage altered in mutant animals. These Findings highlighted the role of low-frequency coding variants in normal-range facial variation.


2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Kristjan Norland ◽  
Gardar Sveinbjornsson ◽  
Rosa B. Thorolfsdottir ◽  
Olafur B. Davidsson ◽  
Vinicius Tragante ◽  
...  

Abstract Features of the QRS complex of the electrocardiogram, reflecting ventricular depolarisation, associate with various physiologic functions and several pathologic conditions. We test 32.5 million variants for association with ten measures of the QRS complex in 12 leads, using 405,732 electrocardiograms from 81,192 Icelanders. We identify 190 associations at 130 loci, the majority of which have not been reported before, including associations with 21 rare or low-frequency coding variants. Assessment of genes expressed in the heart yields an additional 13 rare QRS coding variants at 12 loci. We find 51 unreported associations between the QRS variants and echocardiographic traits and cardiovascular diseases, including atrial fibrillation, complete AV block, heart failure and supraventricular tachycardia. We demonstrate the advantage of in-depth analysis of the QRS complex in conjunction with other cardiovascular phenotypes to enhance our understanding of the genetic basis of myocardial mass, cardiac conduction and disease.


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