Research Roundup, September 7, 2018

Risk scores arise, scrutinizing cells' nutrient sensors, learning about lncRNAs, and more.

Erik Jacobs
Credit: Erik Jacobs

Welcome to the September 7, 2018 installment of Research Roundup, a recurring snapshot of recent studies published by scientists at the Broad Institute and their collaborators.

A calculated risk

Scientists can scan millions of common variants across the genome to estimate risk for complex diseases like breast cancer and heart disease, but more work remains before genetic risk scores become routine clinical tools. On the Broad website we take a deep look at the development of these “polygenic risk scores,” how they are being improved, and how they could one day transform the understanding and prevention of common disease.

Inventory tracking

A variety of sensors feed information to the master regulator mTORC1 about whether the cell has enough nutrients (e.g., amino acids, glucose) to grow and proliferate. In PNAS this week, Kuang Shen and associate member David Sabatini at the Whitehead Institute trace the steps that two of those sensors, Ragulator and SLC38A9, follow to tell mTORC1 when the cell’s lysosomes have plenty of the amino acid arginine. Specifically, Shen and Sabatini showed how the sensors switch two paired proteins, RagA and RagC, into an active state; they in turn give mTORC1 the molecular go-ahead for growth.

Transcription factors and GWAS, genome-wide

A team led by Yakir Reshef and associate member Alkes Price in the Program in Medical and Population Genetics presents a new analysis method — signed linkage disequilibrium profile (SLDP) regression — for quantifying patterns in SNPs’ directional effects on diseases and complex traits. In Nature Genetics, the team describes SLDP regression and demonstrates its use by identifying cases in which SNP alleles’ directions of effect on the binding of a transcription factor (that is, increasing or decreasing binding) systematically correlate with their effect on risk of a disease across the genome. The approach is a powerful new way of leveraging functional genomics data to draw fine-grained biological and mechanistic conclusions from GWAS data.

A quest for immunotherapy contenders

Immunotherapies hold promise against cancer, but determining which patients might benefit the most is challenging. An international team led at the Broad and Dana-Farber Cancer Institute by Cancer Program associate member Eliezer Van Allen studied more than 375 advanced prostate tumors' genomic, transcriptional, and immunological features for hints as to whether those harboring DNA repair problems called “mismatch repair defects” (dMMR) would be good immunotherapy candidates. Their findings, published in the Journal of Clinical Investigation, reveal that dMMR cancers constitute a distinct, aggressive subset of advanced prostate tumors, and might be knocked back by immunotherapies called checkpoint inhibitors. Learn more in Forbes.

Deciphering long non-coding RNAs

Despite the abundance of long non-coding RNAs (lncRNAs) in the human genome, geneticists understand the functions of only a handful of them. A team led by institute director Eric Lander turned their attention to a specific lncRNA called NORAD (or “non-coding RNA activated by DNA damage”). The team describes in Nature how NORAD partners with the protein RBMX to control construction of NARC1, a newly-discovered protein complex that they found helps ensure genome stability. Learn more about NORAD and other lncRNAs in this Q&A with lead author Mathias Munschauer.

To learn more about research conducted at the Broad, visit, and keep an eye on