A functional genomic framework to elucidate novel causal non-alcoholic fatty liver disease genes.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver pathology in western countries, with serious public health consequences. Efforts to identify causal genes for NAFLD have been hampered by the relative paucity of human data from gold-standard magnetic resonance quantification of hepatic fat. To overcome insufficient sample size, genome-wide association studies using NAFLD surrogate phenotypes have been used, but only a small number of loci have been identified to date. In this study, we combined GWAS of NAFLD composite surrogate phenotypes with genetic colocalization studies followed by functional in vitro screens to identify bona fide causal genes for NAFLD. Approach & Results: We used the UK Biobank to explore the associations of our novel NAFLD score, and genetic colocalization to prioritize putative causal genes for in vitro validation. We created a functional genomic framework to study NAFLD genes in vitro using CRISPRi. Our data identify VKORC1, TNKS, LYPLAL1 and GPAM as regulators of lipid accumulation in hepatocytes and suggest the involvement of VKORC1 in the lipid storage related to the development of NAFLD. Conclusions: Complementary genetic and genomic approaches are useful for the identification of NAFLD genes. Our data supports VKORC1 as a bona fide NAFLD gene. We have established a functional genomic framework to study at scale putative novel NAFLD genes from human genetic association studies.

Unsupervised Clustering of Missense Variants in HNF1A Using Multidimensional Functional Data Aids Clinical Interpretation.

Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens.

High Incidence of Heterozygous ABCC8 and HNF1A Mutations in Czech Patients With Congenital Hyperinsulinism.

CONTEXT: Congenital hyperinsulinism of infancy (CHI) represents a group of heterogeneous disorders characterized by oversecretion of insulin from pancreatic ß-cells causing severe hypoglycemia. OBJECTIVE: We studied the distribution of genetic causes of CHI in a Czech population. METHODS: Countrywide collection of patients with CHI included 40 subjects (12 females, median age of diagnosis, 1 wk [interquartile range, 1-612 wk]). We sequenced the ABCC8, KCNJ11, GLUD1, GCK, HADH, UCP2, SLC16A1, HNF4A, and HNF1A genes and investigated structural changes in the ABCC8 gene. We functionally tested novel variants in the ABCC8 gene by Rb(86+) efflux assay and novel variants in the HNF1A gene by transcriptional activation and DNA-binding tests. RESULTS: We found causal mutations in 20 subjects (50%): 19 carried a heterozygous mutation while one patient was homozygous for mutation in the ABCC8 gene. Specifically, we detected 11 mutations (seven novel) in ABCC8, one novel mutation in KCNJ11, five mutations (two novel) in HNF1A, two novel mutations in HNF4A, and one in GCK. We showed a decrease of activation by diazoxide in mutant KATP channels with novel ABCC8 variants by 41-91% (median, 82%) compared with wild-type (WT) channels and reduced transcriptional activity of mutant HNF1A proteins (2.9% for p.Asn62Lysfs93* and 22% for p.Leu254Gln) accompanied by no DNA-binding ability compared with WT HNF1A. CONCLUSION: We detected a higher proportion of heterozygous mutations causing CHI compared with other cohorts probably due to lack of consanguinity and inclusion of milder CHI forms. Interestingly, HNF1A gene mutations represented the second most frequent genetic cause of CHI in the Czech Republic. Based on our results we present a genetic testing strategy specific for similar populations.

Archival bone marrow samples: suitable for multiple biomarker analysis.

AB Archival samples represent a significant potential for genetic studies, particularly in severe diseases with risk of lethal outcome, such as in cancer. In this pilot study, we aimed to evaluate the usability of archival bone marrow smears and biopsies for DNA extraction and purification, whole genome amplification (WGA), multiple marker analysis including 10 short tandem repeats, and finally a comprehensive genotyping of 33,683 single nucleotide polymorphisms (SNPs) with multiplexed targeted next-generation sequencing. A total of 73 samples from 21 bone marrow smears and 13 bone marrow biopsies from 18 Danish and Norwegian childhood acute lymphoblastic leukemia patients were included and compared with corresponding blood samples. Samples were grouped according to the age of sample and whether WGA was performed or not. We found that measurements of DNA concentration after DNA extraction was dependent on detection method and that spectrophotometry overestimated DNA amount compared with fluorometry. In the short tandem repeat analysis, detection rate dropped slightly with longer fragments. After WGA, this drop was more pronounced. Samples stored for 0 to 3 years showed better results compared with samples stored for 4 to 10 years. Acceptable call rates for SNPs were detected for 7 of 42 archival samples. In conclusion, archival bone marrow samples are suitable for DNA extraction and multiple marker analysis, but WGA was less successful, especially when longer fragments were analyzed. Multiple SNP analysis seems feasible, but the method has to be further optimized.

Association of a low-frequency variant in HNF1A with type 2 diabetes in a Latino population.

IMPORTANCE: Latino populations have one of the highest prevalences of type 2 diabetes worldwide. OBJECTIVES: To investigate the association between rare protein-coding genetic variants and prevalence of type 2 diabetes in a large Latino population and to explore potential molecular and physiological mechanisms for the observed relationships. DESIGN, SETTING, AND PARTICIPANTS: Whole-exome sequencing was performed on DNA samples from 3756 Mexican and US Latino individuals (1794 with type 2 diabetes and 1962 without diabetes) recruited from 1993 to 2013. One variant was further tested for allele frequency and association with type 2 diabetes in large multiethnic data sets of 14,276 participants and characterized in experimental assays. MAIN OUTCOME AND MEASURES: Prevalence of type 2 diabetes. Secondary outcomes included age of onset, body mass index, and effect on protein function. RESULTS: A single rare missense variant (c.1522G>A [p.E508K]) was associated with type 2 diabetes prevalence (odds ratio [OR], 5.48; 95% CI, 2.83-10.61; P = 4.4 × 10(-7)) in hepatocyte nuclear factor 1-α (HNF1A), the gene responsible for maturity onset diabetes of the young type 3 (MODY3). This variant was observed in 0.36% of participants without type 2 diabetes and 2.1% of participants with it. In multiethnic replication data sets, the p.E508K variant was seen only in Latino patients (n = 1443 with type 2 diabetes and 1673 without it) and was associated with type 2 diabetes (OR, 4.16; 95% CI, 1.75-9.92; P = .0013). In experimental assays, HNF-1A protein encoding the p.E508K mutant demonstrated reduced transactivation activity of its target promoter compared with a wild-type protein. In our data, carriers and noncarriers of the p.E508K mutation with type 2 diabetes had no significant differences in compared clinical characteristics, including age at onset. The mean (SD) age for carriers was 45.3 years (11.2) vs 47.5 years (11.5) for noncarriers (P = .49) and the mean (SD) BMI for carriers was 28.2 (5.5) vs 29.3 (5.3) for noncarriers (P = .19). CONCLUSIONS AND RELEVANCE: Using whole-exome sequencing, we identified a single low-frequency variant in the MODY3-causing gene HNF1A that is associated with type 2 diabetes in Latino populations and may affect protein function. This finding may have implications for screening and therapeutic modification in this population, but additional studies are required.