Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21276-3</jats:p

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P <5 x 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.Peer reviewe

Distribution of gray matter volume and ‘disinhibition’ scores for brain areas showing a significant interaction between gender and genotype.

<p>Gray matter volume (GMV) in right amygdala (upper row), left orbitofrontal cortex (second row), left dorsolateral prefrontal cortex (third row) and right prefrontal cortex (bottom row) plotted against values on the ‘disinhibition’ subscale of the Three Factor Eating Questionnaire (TFEQ 51) for women (middle column) and men (right column) separately. Left column indicates the brain region where gray matter volume was extracted. Filled dark circles indicate homozygous carriers of the risk allele (CC) at rs17782313, filled gray circles indicate heterozygous subjects (AC) and open circles indicate homozygous carriers of the wildtype allele (AA). pr = partial correlation coefficient controlling for BMI, p = p-value of partial correlation analysis.</p

Detailed demographic and questionnaire data split by rs17782313 near MC4R.

<p>Data are presented as medians and interquartile range in round brackets, 95% confidence intervals of the median based on 1,000 bootstrap samples are given in squared brackets. n: number of participants per category, TFEQ 51: Three Factor Eating Questionnaire, TFEQ R18: Revised and shortened version of the TFEQ, MAF: Minor Allele Frequency (describes the fraction of the minor allele, C, considering the sum of all alleles), p^a: p-value of Kruskal-Wallis one-way analysis of variance, p^b: p-value of Kruskal-Wallis one-way analysis of variance on residuals after correcting for age and BMI. * =  significant (p<.05) association with BMI in linear regression model, ^# = significant (p<.05) association with age in linear regression model.</p

Detailed demographic and questionnaire data split by gender and rs17782313 near MC4R.

<p>Data are presented as medians and interquartile range in round brackets, 95% confidence intervals of the median based on 1,000 bootstrap samples are given in squared brackets. n: number of participants per category, TFEQ 51: Three Factor Eating Questionnaire, TFEQ R18: Revised and shortened version of the TFEQ, MAF: Minor Allele Frequency (describes the fraction of the minor allele, C, considering the sum of all alleles), p^a: p-value of Kruskal-Wallis one-way analysis of variance, p^b: p-value of Kruskal-Wallis one-way analysis of variance on residuals after correcting for age and BMI. * =  significant (p<.05) association with BMI in linear regression model, ^# = significant (p<.05) association with age in linear regression model.</p