Selected Publications

  • The neutral amino acid transporter SLC7A10/ASC-1 is an adipocyte-expressed gene with reduced expression in insulin resistance and obesity. Inhibition of SLC7A10 in adipocytes was shown to increase lipid accumulation despite decreasing insulin-stimulated uptake of glucose, a key substrate for de novo lipogenesis. These data imply that alternative lipogenic substrates to glucose fuel continued lipid accumulation during insulin resistance in obesity.

  • A primary obstacle in translating genetic associations with disease into therapeutic strategies is elucidating the cellular programs affected by genetic risk variants and effector genes. Here, we introduce LipocyteProfiler, a cardiometabolic-disease-oriented high-content image-based profiling tool that enables evaluation of thousands of morphological and cellular profiles that can be systematically linked to genes and genetic variants relevant to cardiometabolic disease. We show that LipocyteProfiler allows surveillance of diverse cellular programs by generating rich context- and process-specific cellular profiles across hepatocyte and adipocyte cell-state transitions. We use LipocyteProfiler to identify known and novel cellular mechanisms altered by polygenic risk of metabolic disease, including insulin resistance, fat distribution, and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse deep phenotypic profiling in lipocytes and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease.

  • Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders.

Wang X, He L, Goggin S, Saadat, A, Wang L, Claussnitzer M*, Kellis M* (*co-senior and co-corresponding). High-resolution genome-wide functional dissection of transcriptional regulatory regions and nucleotides in human. Nature Communications. 2018 Dec 19; 9(1):5380.

  • Genome-wide epigenomic maps have revealed millions of putative enhancers and promoters, but experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited. Here, we present HiDRA (High-resolution Dissection of Regulatory Activity), a combined experimental and computational method for high-resolution genome-wide testing and dissection of putative regulatory regions. We test ~7 million accessible DNA fragments in a single experiment, by coupling accessible chromatin extraction with self-transcribing episomal reporters (ATAC-STARR-seq). By design, fragments are highly overlapping in densely-sampled accessible regions, enabling us to pinpoint driver regulatory nucleotides by exploiting differences in activity between partially-overlapping fragments using a machine learning model (SHARPR-RE). In GM12878 lymphoblastoid cells, we find ~65,000 regions showing enhancer function, and pinpoint ~13,000 high-resolution driver elements. These are enriched for regulatory motifs, evolutionarily-conserved nucleotides, and disease-associated genetic variants from genome-wide association studies. Overall, HiDRA provides a high-throughput, high-resolution approach for dissecting regulatory regions and driver nucleotides.

Quon G, Feizi S, Marbach D, Claussnitzer M, Kellis M. Predicting trait regulators by identifying co-localization of DNA binding and GWAS variants in regulatory regions. bioRxiv 467852. November 11, 2018.

eGTEx Project. Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease. Nat Genet. 2017 Dec;49(12):1664-1670.

Nielson CM, Liu CT, Smith AV, Ackert-Bicknell CL, Reppe S, Johanna J, Wassel C, Register TC, Oei L, Alonso Lopez N, Oei EH, Parimi N, Samelson EJ, Nalls MA, Zmuda J, Lang T, Bouxsein M, Latourelle J, Claussnitzer M, Siggeirsdottir K, Srikanth P, Lorentzen E, Vandenput L, Langefeld C, Raffield L, Terry G, Cox AJ, Allison MA, Criqui MH, Bowden D, Ikram MA, Mellström D, Karlsson MK, Carr J, Budoff M, Phillips C, Cupples LA, Chou WC, Myers RH, Ralston SH, Gautvik KM, Cawthon PM, Cummings S, Karasik D, Rivadeneira F, Gudnason V, Orwoll ES, Harris TB, Ohlsson C, Kiel DP, Hsu YH. Novel Genetic Variants are Associated With Increased Vertebral Volumetric BMD, Reduced Vertebral Fracture Risk, and Increased Expression of SCL1A3 and EPHB2. J Bone Miner Res. 2016 Aug 1.

Claussnitzer M, Dankel SN, Quon G, Kim KH, Meuleman W, Haugen C, Glunk V, Puviindran V, Abdennur N, Liu J, Svensson P, Hsu YH, Mellgren G, Hui CC, Hauner H, Kellis M. FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. The New England Journal of Medicine. 2015. Sep 3;373(10):895-907.

Claussnitzer M, Hui CC, Kellis M. FTO Obesity Variant and Adipocyte Browning in Humans. The New England Journal of Medicine. 2016 Jan 14;374(2):192-3.

Roadmap Epigenomics Consortium, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, Kheradpour P, Zhang Z, Wang J, Ziller MJ, Amin V, Whitaker JW, Schultz MD, Ward LD, Sarkar A, Quon G, Sandstrom RS, Eaton ML, Wu YC, Pfenning AR, Wang X, Claussnitzer M, Liu Y, Coarfa C, Harris RA, Shoresh N, Epstein CB, Gjoneska E, Leung D, Xie W, Hawkins RD, Lister R, Hong C, Gascard P, Mungall AJ, Moore R, Chuah E, Tam A, Canfield TK, Hansen RS, Kaul R, Sabo PJ, Bansal MS, Carles A, Dixon JR, Farh KH, Feizi S, Karlic R, Kim AR, Kulkarni A, Li D, Lowdon R, Elliott G, Mercer TR, Neph SJ, Onuchic V, Polak P, Rajagopal N, Ray P, Sallari RC, Siebenthall KT, Sinnott-Armstrong NA, Stevens M, Thurman RE, Wu J, Zhang B, Zhou X, Beaudet AE, Boyer LA, De Jager PL, Farnham PJ, Fisher SJ, Haussler D, Jones SJ, Li W, Marra MA, McManus MT, Sunyaev S, Thomson JA, Tlsty TD, Tsai LH, Wang W, Waterland RA, Zhang MQ, Chadwick LH, Bernstein BE, Costello JF, Ecker JR, Hirst M, Meissner A, Milosavljevic A, Ren B, Stamatoyannopoulos JA, Wang T, Kellis M. Integrative analysis of 111 reference human epigenomes. Roadmap Epigenomics Consortium. Nature. 2015.

Dankel SN, Svärd J, Matthä S, Claussnitzer M, Klöting N, Glunk V, Fandalyuk Z, Grytten E, Solsvik MH, Nielsen HJ, Busch C, Hauner H, Blüher M, Skurk T, Sagen JV, Mellgren G. COL6A3 Expression in adipocytes associates with insulin resistance and depends on PPARγ and adipocyte size. Obesity. 2014

Claussnitzer M, Dankel SN, Klocke B, Grallert H, Glunk V, Berulava T, Lee H, Oskolkov N, Fadista J, Ehlers K, Wahl S, Hoffmann C, Qian K, Rönn T, Riess L, Müller-Nurasyid M, Skurk T, Bretschneider N, Schroeder T, Skurk T, Horsthemke B, DIAGRAM+ Consortium, Spieler D, Klingenspor M, Seifert M, Kern MJ, Mejhert N, Dahlman I, Hansson O, Hauck S, Blüher, Arner P, Groop L, Illig T, Suhre K, Hsu YH, Mellgren G, Hauner H, Laumen H. Leveraging cross-species transcription factor binding site patterns: from diabetes risk loci to disease mechanisms. Cell. 2014; 156(1-2):343-58.

Claussnitzer M, Skurk T, Hauner H, Daniel H, Rist MJ. Effect of flavonoids on basal and insulin-stimulated-deoxyglucose uptake in adipocytes. Mol Nutr Food Res. 2011 Suppl 1:S26-34.

  • Genomic regions associated with complex traits and diseases are primarily located in non-coding regions of the genome and have unknown mechanism of action. A critical step to understanding the genetics of complex traits is to fine-map each associated locus; that is, to find the causal variant(s) that underlie genetic associations with a trait. Fine-mapping approaches are currently focused on identifying genomic annotations, such as transcription factor binding sites, which are enriched in direct overlap with candidate causal variants. We introduce CONVERGE, the first computational tool to search for co-localization of GWAS causal variants with transcription factor binding sites in the same regulatory regions, without requiring direct overlap. As a proof of principle, we demonstrate that CONVERGE is able to identify five novel regulators of type 2 diabetes which subsequently validated in knockdown experiments in pancreatic beta cells, while existing fine-mapping methods were unable to find any statistically significant regulators. CONVERGE also recovers more established regulators for total cholesterol compared to other fine-mapping methods. CONVERGE is therefore unique and complementary to existing fine-mapping methods and is useful for exploring the regulatory architecture of complex traits.

A full list of publications can be found here.