Transcription Factor KLF14 and Metabolic Syndrome

Yang, Qingchao; Civelek, Mete

doi:10.3389/fcvm.2020.00091

Cited by 33 publications

(25 citation statements)

References 132 publications

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“…Although its direct targets remain to be fully characterized, its effect on the pathology is known to include prevention of cardiovascular disease 37 and suppression of cancers 38 . Computational predictions of its targets include genes that are involved in regulation of cholesterol, body-mass index, insulin and blood glucose level 39 . Although blood was not one of the tissues analyzed in baboons, it is nevertheless noteworthy that methylation of the KLF14 locus in blood of mice is predictive of chronic inflammation in adipose tissue 40 , suggesting that this crosstissue age-associated loci might extend to other tissues and may bear even greater predictive scope.…”

Section: Discussionmentioning

confidence: 99%

Pan-primate DNA methylation clocks

Horvath

Haghani

Zoller

et al. 2020

Preprint

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DNA methylation data have been successfully used to develop highly accurate estimators of age (“epigenetic clocks”) in several mammalian species. With a view of extending epigenetic clocks to primates, we analyzed DNA methylation profiles from five primate species; Papio hamadryas (baboons), Callithrix jacchus (common marmoset), Chlorocebus sabaeus (vervet monkey), Macaca mulatta (rhesus macaque), and Homo sapiens (human). From these we present here, a highly accurate primate epigenetic clock. This clock is based on methylation profiles of CpGs that are highly conserved and are located on a custom methylation array (HorvathMammalMethylChip40). Furthermore, we carried out in-depth analysis of the baboon, as it is evolutionarily the closest primate to humans that can be employed in biomedical research. We present five epigenetic clocks for baboons (Olive-yellow baboon hybrid), one of which, the pan tissue epigenetic clock, was trained on seven tissue types (fetal cerebral cortex, adult cerebral cortex, cerebellum, adipose, heart, liver, and skeletal muscle) with ages ranging from late fetal life to 22.8 years of age. To facilitate translational capability, we constructed two dual-species, human-baboon clocks, whereby one measures ages of both species in units of years, while the other reports ages relative to the maximum lifespan of the species. Although the primate clock applies to all five primate species, the baboon-specific clocks exhibit only moderate age correlations with other primates. We also provide detailed gene and pathway analyses of individual CpGs that relate to age and sex across different primate species. Ten out of 739 sex related CpGs in primate species are located near 9 autosomal genes (including FAM217A, CDYL, POU3F2, and UHRF2). Overall, this study sheds light on epigenetic aging mechanisms in primates, and the potential influence of sex.

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Section: Discussionmentioning

confidence: 99%

Pan-primate DNA methylation clocks

Horvath

Haghani

Zoller

et al. 2020

Preprint

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“…While rs287621 is associated with several adult phenotypes, the strongest known association for rs12672489 is comparative body size at age 10 in the UK Biobank (p < 3.5 × 10 −7 ), showing that this variant influences childhood growth despite residing outside of the region critical for adult traits. eQTL studies have linked variants to the abundance of KLF14 transcript in adipose tissue 40 and a variant near KLF14 has been associated with lower plasma leptin levels 41 , offering a mechanistic hypothesis and yet another putative link between leptin regulation and weight gain in infancy.…”

Section: Resultsmentioning

confidence: 99%

Characterization of the genetic architecture of BMI in infancy and early childhood reveals age-specific effects and implicates pathways involved in Mendelian obesity

Helgeland

Vaudel

Solé-Navais

et al. 2021

Preprint

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To elucidate the role of common genetic variation on infant and child weight development, we performed genome-wide association studies across 12 time points from birth to eight years in 28,681 children and their parents (27,088 mothers and 26,239 fathers) in the Norwegian Mother, Father and Child Cohort Study (MoBa). We identify 46 distinct loci associated with early childhood BMI at specific ages, matching different child growth phases, and representing four major trajectory patterns. Among these loci, 30 are independent of known birth weight and adult BMI loci, and 21 show peak effect between six months and three years, making these discoverable only at early age. Several of the 21 variants reside in/near genes previously implicated in severe forms of early-onset obesity, and monogenic obesity genes are enriched in the vicinity of the 46 loci. Four loci demonstrate evidence of several independent association signals as key drivers for BMI development near LEPR, GLP1R, PCSK1, and KLF14, all central to appetite and energy balance. At the KLF14 locus, we detect significant associations for maternally inherited alleles only, consistent with imprinting effects. Finally, we demonstrate how the BMI distribution stratified by different polygenic risk scores transitions from birth to adult profile throughout early childhood, and how age-specific polygenic risk scores improve the prediction of childhood obesity, outperforming scores based on adult BMI. In conclusion, our results offer a fine-grained characterization of the rapidly changing genetic association landscape sustaining early growth.

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“…The KLF14 (Krüpple-Like family 14) transcription factor is associated with metabolic syndrome and regulates gene expression in adipose tissue. This single exon gene is imprinted and only expressed from the maternally inherited allele 32 , and is expressed more highly in females than males 22 . Homozygous females with the KLF14 risk allele had significantly larger SAT white adipocytes in the Oxford Biobank (BMI-matched) 13 and GTEx (unmatched) 11 datasets, compared to non-risk homozygous females.…”

Section: Introductionmentioning

confidence: 99%

“…Obesity has reached pandemic levels and is strongly associated with a higher risk of type 2 diabetes, cardiovascular disease and cancer, as well as other chronic diseases such as fatty liver disease, hyperlipidaemia, hypertension, gout, restrictive lung disease, stroke, dementia, gallbladder disease, degenerative arthritis, and infertility (Blüher, 2019;Hausman et al, 2001;Myint et al, 2014;Pulit et al, 2019;Vazquez et al, 2007;Verboven et al, 2018). Where the expansion occurs is also important, as VAT expansion (especially omental and mesenteric) is correlated with higher disease risk, whereas SAT expansion can have a protective metabolic effect (Kim et al, 2007;Kusminski et al, 2012;Tchkonia et al, 2013;Yang and Civelek, 2020). Further, relative anthropometric measures of fat distribution such as waist-hip-ratio adjusted for BMI (WHRadjBMI) capture body fat percentage, and cardiovascular disease and type 2 diabetes risk, and may be better than BMI measures (Dale Caroline E. et al, 2017;Pulit et al, 2019;Winkler et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Phenotyping of Klf14 mouse white adipose tissue enabled by whole slide segmentation with deep neural networks

Casero

Westerberg

Horner

et al. 2021

Preprint

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White adipose tissue (WAT) plays a central role in metabolism, and multiple diseases and genetic mutations cause its remodeling, most notably obesity, which has reached pandemic levels. WAT is present in subcutaneous (SAT) and visceral (VAT) depots, and its main components are white adipocytes. Quantitative analysis of white adipocyte size and counts is of great interest to understand physiology and disease, due to intra- and inter-depot heterogeneity, as well as better prognosis for hypertrophy than hyperplasia, and for SAT expansion than VAT expansion. H&E histology of whole depot cross-sections provides excellent approximation of cell morphology and preserves spatial information. Previous studies have been limited to window subsampling of whole slides, and cell size analysis. In this paper, we present a deep learning pipeline that can segment overlapping white adipocytes on whole slides and filter out other cells. We also propose a statistical framework based on linear models to study WAT phenotypes with three interconnected levels (body weight BW, depot weight DW and quartile cell area). Applying it to find Klf14 phenotypes in mice using 147 whole slides of WAT H&E histology, we show sexual dimorphism, and different effects between depots, heterozygous parent of origin for the KO allele and genotype (WT vs. Het). In particular, whether variables are correlated (DW vs. BW and cell area vs. DW), and statistical differences between fitted linear models. We also find significant differences between hand-traced or window subsampling datasets and whole slide analysis. Finally, we provide heatmaps of cell size for all the slides, showing substantial spatial heterogeneity and local spatial correlations.

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Transcription Factor KLF14 and Metabolic Syndrome

Cited by 33 publications

References 132 publications

Pan-primate DNA methylation clocks

Pan-primate DNA methylation clocks

Characterization of the genetic architecture of BMI in infancy and early childhood reveals age-specific effects and implicates pathways involved in Mendelian obesity

Phenotyping of Klf14 mouse white adipose tissue enabled by whole slide segmentation with deep neural networks

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