Omics update

My latest Science Magazine arrived the other day.

"Special Issue: Single-Cell Genomics?" Interesting.

INTRODUCTION TO SPECIAL ISSUE
A Fantastic Voyage in Genomics
Laura M. Zahn

Imagine being able to shrink down to a small enough size to peer into the human body at the single-cell level. Now take a deep breath and plunge into that cell to see all of the ongoing biological processes, including the full complement of molecules and their locations within the cell. This has long been the realm of science fiction, but not for much longer. Recent technological advances now allow us to identify and visualize RNA transcripts, proteins, and other cellular components at the single-cell level. This has led to discoveries about the immune system, brain, and developmental processes and is poised to revolutionize our understanding of the entire human body.

We anticipate breakthroughs with an increased ability to confidently examine the components of a single cell, including in identifying and treating disease at the cellular or even molecular level. Advancing our understanding of pathology will allow us to predict how genes predispose individuals to a disease and aid in prevention and treatment. This will be especially important for diseases such as cancer, which can often have extremely variable genetic compositions resulting in different gene expression profiles within a single tumor. Although the technology to shrink oneself remains fiction, our ability to visualize how genes act at the single-cell level is not, and we look forward to enlarging our knowledge of the human body.

Abstract
The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology. Here we provide an overview of the state of single-cell genomics methods and an outlook on the use of single-cell techniques to decipher the adaptive and innate components of immunity.

Abstract
The stereotyped spatial architecture of the brain is both beautiful and fundamentally related to its function, extending from gross morphology to individual neuron types, where soma position, dendritic architecture, and axonal projections determine their roles in functional circuitry. Our understanding of the cell types that make up the brain is rapidly accelerating, driven in particular by recent advances in single-cell transcriptomics. However, understanding brain function, development, and disease will require linking molecular cell types to morphological, physiological, and behavioral correlates. Emerging spatially resolved transcriptomic methods promise to fill this gap by localizing molecularly defined cell types in tissues, with simultaneous detection of morphology, activity, or connectivity. Here, we review the requirements for spatial transcriptomic methods toward these goals, consider the challenges ahead, and describe promising applications.

Abstract
Single-cell multi-omics has recently emerged as a powerful technology by which different layers of genomic output—and hence cell identity and function—can be recorded simultaneously. Integrating various components of the epigenome into multi-omics measurements allows for studying cellular heterogeneity at different time scales and for discovering new layers of molecular connectivity between the genome and its functional output. Measurements that are increasingly available range from those that identify transcription factor occupancy and initiation of transcription to long-lasting and heritable epigenetic marks such as DNA methylation. Together with techniques in which cell lineage is recorded, this multilayered information will provide insights into a cell’s past history and its future potential. This will allow new levels of understanding of cell fate decisions, identity, and function in normal development, physiology, and disease.

Firewalled, AAAS members only. Or, you can buy the hardcopy at a newsstand or read it at a library.

Lots of detail, mostly over my head, but important stuff. I have to wonder how far away these research developments are from widespread applied clinical tx practice?

Some reporting on the topic from H&HN:

Genomic Medicine Has Entered the Building
With game-changing promises starting to pay off, hospitals need to start preparing now for the changes genomics will bring

After years of fanfare and a few false starts, the era of genomic medicine has finally arrived.

Across the country, thousands of patients are being treated, or having their treatment changed, based on information gleaned from their genome. It’s a revolution that has been promised since the human genome was first published in 2001. But making it real required advances in information technology infrastructure and a precipitous drop in price.

Today, the cost of whole exome sequencing, which reveals the entire protein-coding portion of DNA, is roughly equivalent to an MRI exam in many parts of the country, says Louanne Hudgins, M.D., president of the American College of Medical Genetics and Genomics and director of perinatal genetics at Lucile Packard Children's Hospital Stanford, Palo Alto, Calif.

“Genomic sequencing is a tool like any other tool in medicine, and it’s a noninvasive tool that continues to provide useful information for years after it is performed,” she says…

"Treating genes, not organs"

Let's hope. Read all of it.

I've had a recurrent go at "Omics" topics before, e.g., here, and here. See also my post on "Personalized Medicine."

Below, apropos?

NEXT UP AT HEALTH 2.0

How Technology Development and Big Data are Affecting the Transformation of Health Care
               
Precision Medicine has come a long way in the last 10+ years thanks to advances in diagnostics, computing, and consumer tools. The ongoing quest to better understand disease predisposition and prevention through genomic and environmental factors is key to increasing the quality and length of life. Technology for Precision Health will explore how technology can help.

How can we think differently about gathering, analyzing and sharing information? Which incentives can be offered to structurally change the system toward longer term care of patients? Which mechanisms will empower patients with their data and create virtuous partnerships with providers to truly drive value? Conference delegates will learn about the latest tools in Precision Medicine and Health as well as be part of the discussion on new ontologies and policy changes needed to bring these technologies to patients...

Click here (or the above headline) for the site link.

Also of pertinence, from the NEJM:

Lost in Thought — The Limits of the Human Mind and the Future of Medicine
Ziad Obermeyer, M.D., and Thomas H. Lee, M.D.

In the good old days, clinicians thought in groups; “rounding,” whether on the wards or in the radiology reading room, was a chance for colleagues to work together on problems too difficult for any single mind to solve.
Today, thinking looks very different: we do it alone, bathed in the blue light of computer screens.

Our knee-jerk reaction is to blame the computer, but the roots of this shift run far deeper. Medical thinking has become vastly more complex, mirroring changes in our patients, our health care system, and medical science. The complexity of medicine now exceeds the capacity of the human mind.

Computers, far from being the problem, are the solution. But using them to manage the complexity of 21st-century medicine will require fundamental changes in the way we think about thinking and in the structure of medical education and research.

It’s ironic that just when clinicians feel that there’s no time in their daily routines for thinking, the need for deep thinking is more urgent than ever. Medical knowledge is expanding rapidly, with a widening array of therapies and diagnostics fueled by advances in immunology, genetics, and systems biology. Patients are older, with more coexisting illnesses and more medications. They see more specialists and undergo more diagnostic testing, which leads to exponential accumulation of electronic health record (EHR) data. Every patient is now a “big data” challenge, with vast amounts of information on past trajectories and current states.

All this information strains our collective ability to think. Medical decision making has become maddeningly complex. Patients and clinicians want simple answers, but we know little about whom to refer for BRCA testing or whom to treat with PCSK9 inhibitors. Common processes that were once straightforward — ruling out pulmonary embolism or managing new atrial fibrillation — now require numerous decisions.

So, it’s not surprising that we get many of these decisions wrong…

Open access. Read all of it.

"Computers, far from being the problem, are the solution. But using them to manage the complexity of 21st-century medicine will require fundamental changes in the way we think about thinking and in the structure of medical education and research."

Also of note, our hardy perennial, EHR lamentation. From THCB:

EHR-Driven Medical Error: The Unknown and the Unknowable
BY ROSS KOPPEL

Politico’s Arthur Allen has written a useful report on recent findings about EHR-related errors. We must keep in mind, however, that almost all EHR-related errors are unknown, and often unknowable. Why?...

Interesting post. I'd like to have Dr. Jerome Carter's reaction. See also my prior post "Are structured data now the enemy..."

TWO NEW READS UNDERWAY

"Machine Learning" looks to be partially a bit remedial for me (e.g., regression models and decision trees), but looks like a good quick tutorial. "The Influential Mind" goes to my abiding interest in cognitive/neuroscience topics. Stay tuned.

A SAD CODA

Seattle's AI entrepreneur Matt Bencke has died, losing his fight against stage IV metatstatic pancreatic cancer. He was only 45. Very sad. I have followed developments closely, given that my 47 yr old daughter has a very similar dx.

Rachel Lerman of The Seattle Times has a fine story on Matt. My heart goes out to his family and friends.
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More to come...