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Liquid Biopsy Proteomics and AI Identify Cellular Drivers of Eye Aging

Researchers developed a technology called TEMPO, which integrates microvolume liquid-biopsy proteomics, single-cell transcriptomics, and AI, to map almost…

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Researchers headed by a team at Stanford University have mapped almost 6,000 proteins from different cell types within the eye by analyzing tiny drops of eye fluid that are routinely removed during surgery. The team developed an approach, called TEMPO ((tracing expression of multiple protein origins), that integrates microvolume liquid-biopsy proteomics, single-cell transcriptomics, and AI, to generate a “proteomic clock” that can predict a healthy person’s age based on their protein profile.

The clock revealed that diseases such as diabetic retinopathy and uveitis cause accelerated aging within specific cell types. Surprisingly, the researchers also detected proteins associated with Parkinson’s disease (PD) within eye fluid, which they say could offer a pathway to earlier Parkinson’s diagnoses.

“What’s amazing about the eye is we can look inside and see diseases happening in real time,” Vinit Mahajan, MD, PhD, surgeon and professor of ophthalmology at Stanford University. “Our primary focus was to connect those anatomical changes to what’s happening at the molecular level inside the eyes of our patients.” Mahajan is senior author of the team’s published paper in Cell, titled “Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.” In their report they concluded, “Application of TEMPO could be transformative toward identifying cellular mechanisms, enhancing diagnosis, optimizing clinical trials, and determining the interplay between aging and disease.”

The eye is a difficult organ to sample in living patients because, like the brain, it is non-regenerative, and taking a tissue biopsy would cause irreparable damage. As the authors noted, “In particular, cell-level analysis has been severely limited in non-regenerative organs and tissues, such as the brain and the retina, because direct biopsies would cause serious, irreversible functional damage.” An alternative method is to use liquid biopsies, which are samples of fluid taken from near the cells or tissues of interest. The approach does have limitations, however. While liquid biopsies can provide a snapshot of what proteins are present in the region of interest, to date they have been limited in their ability to measure large numbers of proteins within the small volumes of fluid. They are also unable to provide information on which cells produced which proteins, which is important for diagnosing and treating diseases. “… current analyses cannot resolve proteins at refined cellular resolution,” the team continued.

The multi-modal TEMPOapproach developed by Mahajan and colleagues combines proteomics in cells acquired in microvolume liquid biopsies, with single-cell transcriptomics techniques, and AI, to addresses these limitations, and “… resulting in a powerful and minimally invasive tool to examine disease and aging mechanisms at the cell level in vivo,” they stated. To map protein production by different types of cells within the eye, the researchers applied the platform to characterize proteins in 120 liquid biopsies taken from the aqueous humor (AH) or vitreous humor (VH) of patients undergoing eye surgery.  They identified 5,953 proteins—ten times the number of proteins previously characterized in similar studies, and were then able to trace each protein back to specific cell types.

Eye fluid in a cryovial [Teja Chemudupati]
To investigate the relationship between disease and molecular aging, the researchers then built an AI machine learning model that can predict the molecular age of the eye based on a subset of 26 proteins. The model was able to accurately predict the age of healthy eyes but showed that diseases were associated with significant molecular aging. For diabetic retinopathy (DR), the degree of aging increased with disease progression and this aging was accelerated by as much as 30 years for individuals with severe (proliferative) diabetic retinopathy. These signs of aging were sometimes observable before the patient displayed clinical symptoms of the underlying disease and lingered in patients who had been successfully treated. “Most surprising in our study was that diabetic patients without any clinical evidence of retinopathy showed molecular evidence of accelerated cell aging,” the team stated. “This clearly supports molecular assessment of cell-type-specific aging as a valuable adjunct to the currently used clinical imaging techniques and that earlier preventive interventions may be beneficial.”

The study also discovered evidence that immune cells are involved in later-stage DR, and found an increase in liver-derived proteins in the AH of DR patients. “TEMPO, as applied to AH liquid biopsies, has uncovered a role for specific immune cells and liver proteins in DR, which could change therapeutic strategies,” the scientists wrote. “To our knowledge, this is the first in vivo human molecular data demonstrating that immune cells, such as macrophages, are important molecular drivers of late-stage DR.” The liver proteins identified are known to be involved in inflammatory processes, and this, the team noted, raises the possibility that the liver may directly contribute to inflammation in DR pathology, “… indicating that systemic therapeutic intervention may be beneficial.”

The researchers in addition detected several proteins that are associated with Parkinson’s disease. These proteins are usually only identified post mortem, and current diagnostic methods aren’t capable of testing for them, which is one reason Parkinson’s diagnoses are so difficult. Screening for these markers in eye fluid could potentially enable earlier diagnosis of Parkinson’s disease and later therapeutic monitoring. “Neurodegenerative diseases, such as PD, often represent a diagnostic challenge and may not be definitively diagnosed without a postmortem examination,” they wrote. “Here, we show the potential of using AH liquid biopsies as a valuable tool for diagnostic and prognostic assessment of brain disease … These results redefine the PD phenotype in the retina at a molecular and cell level and highlight the potential of AH liquid biopsies as a valuable tool for diagnostic assessment or even molecular monitoring of PD therapies.”

The authors say that their collective results suggest that aging may be organ- or even cell-specific, which could yield advances in precision medicine and clinical trial design. “These findings demonstrate that our organs are aging at different rates,” said first author and ophthalmologist Julian Wolf, MD, at Stanford University. “The use of targeted anti-aging drugs could be the next step in preventative, precision medicine.”

Added Mahajan, “If we’re going to use molecular therapies, we should be characterizing the molecules in our patients. I think reclassifying patients based on their molecular patterns and which cells are being affected can really improve clinical trials, drug selection, and drug outcomes.”

Next, the researchers plan to characterize samples from a larger number of patients and a broader range of eye diseases. They also say that their method could be used to characterize other difficult-to-sample tissues. For example, liquid biopsies of cerebrospinal fluid could be used to study or diagnose the brain, synovial fluid could be used to study joints, and urine could be used to study the kidneys. In their paper the investigators concluded, “Our approach, which can be applied to other organ systems, has the potential to transform molecular diagnostics and prognostics while uncovering new cellular disease and aging mechanisms …  TEMPO fills a critical gap in the ability to study human disease and aging at the molecular and cellular levels in living humans.”

The post Liquid Biopsy Proteomics and AI Identify Cellular Drivers of Eye Aging appeared first on GEN - Genetic Engineering and Biotechnology News.

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Realtor.com Reports Active Inventory UP 15.7% YoY; New Listings up 10.9% YoY

What this means: On a weekly basis, Realtor.com reports the year-over-year change in active inventory and new listings. On a monthly basis, they report total inventory. For January, Realtor.com reported inventory was up 7.9% YoY, and down 40% compare…

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What this means: On a weekly basis, Realtor.com reports the year-over-year change in active inventory and new listings. On a monthly basis, they report total inventory. For January, Realtor.com reported inventory was up 7.9% YoY, and down 40% compared to January 2019. Now - on a weekly basis - inventory is up 15.7% YoY, and that would put inventory still down about 39% compared to February 2019.

Realtor.com has monthly and weekly data on the existing home market. Here is their weekly report: Weekly Housing Trends View — Data Week Ending February 17, 2024
Active inventory increased, with for-sale homes 15.7% above year ago levels.

For a 15th consecutive week, active listings registered above prior year level, which means that today’s home shoppers have more homes to choose from that aren’t already in the process of being sold. So far this season, the increase in newly listed homes has resulted in a boost to overall inventory, but while the added inventory has certainly improved conditions from this time in 2021 through 2023, overall inventory is still low compared to the same time in February 2020 and years prior to the COVID-19 Pandemic.

New listings–a measure of sellers putting homes up for sale–were up this week, by 10.9% from one year ago.

Newly listed homes were above last year’s levels for the 17th week in a row, which could further contribute to a recovery in active listings meaning more options for home shoppers. This past week, newly listed homes were up 10.9% from a year ago, accelerating slightly from the 9.5% growth rate seen in the previous week.
Here is a graph of the year-over-year change in inventory according to realtor.com

Inventory was up year-over-year for the 154th consecutive week following 20 consecutive weeks with a YoY decrease in inventory.  

Inventory is still historically very low.

Although new listings remain well below "typical pre-pandemic levels", new listings are now up YoY for the 17th consecutive week.

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Positioning Is Worrying And Nobody Seems To Care

Positioning Is Worrying And Nobody Seems To Care

By Jan-Patrick Barnert and Michael Msika, Bloomberg Markets Live reporters and strategists

The…

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Positioning Is Worrying And Nobody Seems To Care

By Jan-Patrick Barnert and Michael Msika, Bloomberg Markets Live reporters and strategists

The market was braced for Nvidia’s earnings and they lived up to expectations, while the Fed minutes were pretty much a non-event. But the big picture is worrying: positioning is stretched and most investors don’t seem to care.

Some profit taking on tech stocks before the most anticipated earnings release of the season was hardly surprising. But now that Nvidia is out of the way, with the stock gaining 9% in post market trading, the big question is what investors will do about their very stretched equity exposure: build more, hold or start to unwind soon?

So far, portfolio managers have been busy buying into a bull trend perceived to have no ending. The Stoxx 600 is closing in on a record high and overbought levels, while CFTC future net positioning in dollar terms on the S&P 500 reached an all-time high earlier this month.

“Even post Tuesday’s selloff, indications of short-term US equity positioning remain stretched with quant funds, levered upside, momentum and call skew all more than two-thirds of the way to the levels that preceded two of the four largest S&P fragility events since 1928: Feb. 2018’s ‘Vixplosion’ and March 2020’s Covid shock,” say Bank of America derivatives strategists including Vittoria Volta. “With the pressure to chase momentum and fickle liquidity, fragility risks are high, though not extreme.”

That said, the strategists don’t see a bubble forming for the Magnificent 7 as their volatility has been falling, unlike during bubble episodes when price swings became more pronounced in concert with rising prices. “The decoupling between upside and downside vol in these stocks is reminiscent of the 2000s tech bubble, but earnings better meeting price-expectations and the asymmetry in Mag7’s macro reaction function suggests that this trend may be more due to the pain trade still being higher,” they say.

Europe hasn’t been immune to the tech hype — on the contrary. Tech is among the best performing Stoxx 600 sectors this year after a 9.1% surge, while ASML and SAP alone are responsible for a third of the benchmark’s gains and nearly half of the returns in the Euro Stoxx 50. Meanwhile, according to the BofA European fund managers survey, tech is now the most popular industry group, along with insurance. Following a massive surge in exposure last month, a net 32% of BofA’s respondents said they overweight the sector.


 
At the same time, tech sector breadth as measured by the short-term indicator of stocks trading above their 50-day moving average has weakened further. The indicator failed to confirm a top in the market as it had done multiple times over the past 18 months and instead decoupled from the wider benchmark as performance has become increasingly concentrated within a handful of stocks. This is most notable in the Nasdaq, where Nvidia and Meta account for almost 70% of this year’s gains.

Overall, describing markets as calm sounds increasingly like an understatement — at least when using the favored VIX curve indicator, which has now fallen to the lowest level since 2017. Together with a collapsing skew reading for the wider market and especially for tech stocks, plus a put-call ratio below 0.8, all the signs suggest that just about nobody cares about downside risk at this point.

Nomura cross-asset strategist Charlie McElligott explains it thus: “The key to equities seemingly being able to keep shaking off nascent pullbacks? Well outside of the ongoing ‘AI euphoria’ theme and de-grossing of shorts, which continues powering spectacular rallies in the ‘worst of’ junk companies, it’s been all about the Pavlovian ‘Options Selling’ — flows which continue to suppress volatility.”

And while this low-volatility, high-momentum market environment that’s free of big moves has encouraged almost every systematic investor from vol control to trend followers toward near-maximum exposure, their impact is subdued for the moment. But their positioning could act as a combustive agent if things go wrong.

“Just like gamma exposure, systematic flows aren’t always about direction; sometimes, they can simply act as stabilizing forces in the market,” say Tier1Alpha strategists. “That said, these funds still pose a significant risk to the equities market this week, as even a small uptick in volatility could result in some significant selling.”

“Across sector groups, positioning in mega-cap growth and tech continues to rise and is into the top decile, with net call volume surging to pandemic boom levels this week while flows into tech funds also resumed their strong run,” according to Deutsche Bank strategists Parag Thatte and Bankim Chadha. They add that equity allocations by CTAs rose further last week to hit the 83rd percentile.

Tyler Durden Thu, 02/22/2024 - 11:55

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The US Leading Economic Index Takes One For The Team

It was probably inevitable, but it’s striking nonetheless. The once-reliable US Leading Economic Index (LEI) has been signaling a US recession for more…

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It was probably inevitable, but it’s striking nonetheless. The once-reliable US Leading Economic Index (LEI) has been signaling a US recession for more than a year but the economy has continued to expand. It’s a teachable moment in recession nowcasting and forecasting, but not surprising. The main takeaway, again: every recession indicator fails, eventually.

Why? It’s the nature of recessions. Every downturn’s different, the byproduct of a unique set of factors at a given point in time. There are similarities, but not enough so that you can easily select a handful of indicators that worked the last time and assume they’ll remain forever relevant in signaling future contractions.

The lesson, which I’ve been preaching for years – and is the core principle for The US Business Cycle Risk Report – is that the closest mere mortals can come to a “reliable” recession nowcasting/forecasting methodology is to aggregate signals from multiple, complimentary models.

But even combining models doesn’t suffice, if you pick a few and assume you’re done. There’s always room for improvement, in part because the economy is continually evolving, which may render a seemingly robust modeling effort less than robust at some point.

Keeping an eye open for new ways to profile the business cycle, in other words, is a key part of the analytics. For example, as I discussed earlier this week, aggregating state coincident indexes from the bottom up offers a potentially new and useful tool for enhancing existing recession nowcasting/forecasting analytics.

Meanwhile, what happened to the LEI? Ed Yardeni at YardeniQuicktakes.com sums up the problem:

The Conference Board, which compiles the two indexes, backed off its recession forecast. A spokesperson for the group said: “While the declining LEI continues to signal headwinds to economic activity, for the first time in the past two years, six out of its 10 components were positive contributors over the past six-month period (ending in January 2024).” She added. “As a result, the leading index currently does not signal recession ahead. While no longer forecasting a recession in 2024, we do expect real GDP growth to slow to near zero percent over Q2 and Q3.”

Rather than admit that the LEI has been misleading, The Conference Board tweaked the rule of thumb, which had been that three consecutive declines in the LEI signaled a looming recession. Now it’s how many of its components are falling over a six month period. In our opinion, the LEI is due for a product recall. It needs to be fixed to give more weight to the services sector. Here is January’s LEI contributions chart:

To be fair, the economy in the post-pandemic period has surprised on multiple fronts. My efforts at trying to screen out the noise from the signal have been affected, too, albeit temporarily, in late-2022, when it appeared that the US was on the verge of slipping into an NBER-defined recession. But by the spring of 2023, the signs were accumulating that the recession warning, which never reached a tipping point, was fading. Notably, the cornerstone of The US Business Cycle Risk Report – the Composite Recession Probability (CRPI) Index, which aggregates several business-cycle benchmarks — had pulled back from a moderate but not decisive recession warning in early 2023. Here’s how CRPI stacked up in mid-April 2023:

For comparison, here’s CRPI’s reading at last week’s close (Feb. 16):

To clear, there’s never 100% certainly in real time about estimating recession risk. It’s always possible that some new twist has rendered even the best of methodologies null and void at times.

The good news is that there’s a productive path to reduce the risk of failure and it starts by carefully diversifying the indicators that inform your analysis. For those who ignore this rule, a trap awaits: Every business-cycle indicator fails eventually. Fortunately, there’s a solution via the observation that there’s strength in numbers. Although any one recession indicator will likely fail at times, it’s highly unlikely that every indicator will fail simultaneously.  


How is recession risk evolving? Monitor the outlook with a subscription to:
The US Business Cycle Risk Report


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