Identification of a 1p21 independent functional variant for abdominal obesity

PTBP2 - a gene with relevance for both Anorexia nervosa and body weight regulation

Genetic factors are relevant for both eating disorders and body weight regulation. A recent genome-wide association study (GWAS) for anorexia nervosa (AN) detected eight genome-wide significant chromosomal loci. One of these loci, rs10747478, was also genome-wide and significantly associated with body mass index (BMI). The nearest coding gene is the Polypyrimidine Tract Binding Protein 2 gene (PTBP2). To detect mutations in PTBP2, Sanger sequencing of the coding region was performed in 192 female patients with AN (acute or recovered) and 191 children or adolescents with (extreme) obesity. Twenty-five variants were identified. Twenty-three of these were predicted to be pathogenic or functionally relevant in at least one in silico tool. Two novel synonymous variants (p.Ala77Ala and p.Asp195Asp), one intronic SNP (rs188987764), and the intronic deletion (rs561340981) located in the highly conserved region of PTBP2 may have functional consequences. Ten of 20 genes interacting with PTBP2 were studied for their impact on body weight regulation based on either previous functional studies or GWAS hits for body weight or BMI. In a GWAS for BMI (Pulit et al. 2018), the number of genome-wide significant associations at the PTBP2 locus was different between males (60 variants) and females (two variants, one of these also significant in males). More than 65% of these 61 variants showed differences in the effect size pertaining to BMI between sexes (absolute value of Z-score >2, two-sided p < 0.05). One LD block overlapping 5'UTR and all coding regions of PTBP2 comprises 56 significant variants in males. The analysis based on sex-stratified BMI GWAS summary statistics implies that PTBP2 may have a more pronounced effect on body weight regulation in males than in females.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

Mendelian Randomization Analysis Reveals Causal Effects of the Human Gut Microbiota on Abdominal Obesity

BACKGROUND

Although recent studies have revealed an association between the composition of the gut microbiota and obesity, whether specific gut microbiota cause obesity has not been determined.

OBJECTIVES

The aim of this study is to determine the causal relationship between specific gut microbiota and abdominal obesity. Based on genome-wide association study (GWAS) summary statistics, we performed a 2-sample Mendelian randomization (MR) analysis to evaluate whether the gut microbiota affects abdominal obesity.

METHODS

Gut microbiota GWAS in 1126 twin pairs (age range, 18-89 years; 89% were females) from the TwinsUK study were used as exposure data. The primary outcome tested was trunk fat mass (TFM) GWAS in 492,805 participants (age range, 40-69 years; 54% were females) from the UK Biobank. The gut microbiota were classified at family, genus, and species levels. A feature was defined as a distinct family, genus, or species. MR analysis was mainly performed by an inverse variance-weighted test or Wald ratio test, depending on the number of instrumental variables (IVs) involved. A sensitivity analysis was performed on significant results by a weighted median test and a weighted genetic risk score (GRS) analysis.

RESULTS

Results of MR analyses provided evidence of a causal association between 3 microbiota features and TFM, including 1 family [Lachnosiraceae; P = 0.02; β = 0.001 (SEE, 4.28 × 10-4)], 1 genus [Bifidobacterium; P = 5.0 × 10-9; β = -0.08 (SEE, 0.14)], and 1 species [Prausnitzii; P = 0.03; β = -0.007 (SEE, 0.003)]. Both the weighted median test and GRS analysis successfully validated the association of the genetically predicted family, Lachnosiraceae (Pweighted median = 0.03; PGRS = 0.004).

CONCLUSIONS

Our findings provided evidence of a causal association between gut microbiota and TFM in UK adults and identified specific bacteria taxa that may regulate the fat metabolism, thus offering new direction for the treatment of obesity.

Identification of Candidate Genes Associated with Susceptibility to Ovarian Clear Cell Adenocarcinoma Using cis-eQTL Analysis

Ovarian clear cell adenocarcinoma (Ov-CCA) has a higher prevalence in the Japanese ancestry than other populations. The ancestral disparities in Ov-CCA prevalence suggests the presence of Ov-CCA-specific genetic alterations and may provide an opportunity to identify the novel genes associated with Ov-CCA tumorigenesis. Using 94 previously reported genes as the phenotypic trait, we conducted multistep expression quantitative trait loci (eQTL) analysis with the HapMap3 project datasets. Four single-nucleotide polymorphisms (SNPs) (rs4873815, rs12976454, rs11136002, and rs13259097) that had different allele frequencies in the Japanese ancestry and seven genes associated in cis (APBA3, C8orf58, KIAA1967, NAPRT1, RHOBTB2, TNFRSF10B, and ZNF707) were identified. In silico functional annotation analysis and in vitro promoter assay validated the regulatory effect of rs4873815-TT on ZNF707 and rs11136002-TT on TNFRSF10B. Furthermore, ZNF707 was highly expressed in Ov-CCA and had a negative prognostic value in disease recurrence in our sample cohort. This prognostic power was consistently observed in The Cancer Genome Atlas (TCGA) clear cell renal cell carcinoma dataset, suggesting that ZNF707 may have prognostic value in clear cell histology regardless of tissue origin. In conclusion, rs4873815-TT/ZNF707 may have clinical significance in the prognosis and tumorigenesis of Ov-CCA, which may be more relevant to clear cell histology. Besides, this study may underpin the evidence that cis-eQTL analysis based on ancestral disparities can facilitate the discovery of causal genetic alterations in complex diseases, such as cancer.