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bug-punk:shadow-banned-the-hedgehog:I feel like the original Chinese ending is e...
Saturday December 6^th, 2025 at 12:15 AM

999 thou short of a mill

shadow-banned-the-hedgehog:
I feel like the original Chinese ending is even funnier than the translation implies. My inexpert tweaks:

“Heterosexuality really is the most fragile type of sexual orientation in the world, in human history electric shock, detention, family coercion, campus and workplace bullying all were unable to change homosexuality to heterosexuality, but heterosexuals need only get a glimpse of homosexual information and movies and they can turn into homosexual”

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sarcozona

55 minutes ago

Epiphyte City

2025-11-14 BC by Ducky
Saturday December 6^th, 2025 at 12:12 AM

Pandemics in British Columbia

Charts

DAMMIT. The province is not going to give us the number of people with COVID-19 in hospital any more.

From the Viral Pathogen Characterization page:

I would like to point out that for the past three years, the peaks of COVID-19 cases (as measured by the province) have all been in early October or late September. (Note that it’s a lot harder to spot any seasonality in the wastewater levels, so the case count might reflect who-gets-tested more than what-is-circulating. I would say, “maybe people don’t get tested around the holidays”, except that clearly they do — see how large the flu and RSV peaks are around the holidays.)

In the most recent data (ending 8 Nov) as reported on 13 Nov 2025, among influenza-like illness (i.e upper respiratory diseases) cases the province has test data for:

31.6% were COVID-19;
26.6% were entero/rhinoviruses;
21.7% were influenza A or B;
7.7% were RSV;
7.5% were parainfluenza;
2.4% were metapneumonia viruses;
2.0% were adenoviruses;
0.5% were “common cold” coronaviruses.

Wastewater

From Jeff’s wastewater spreadsheet:

Wastewater levels are not the lowest they’ve been in the past few years, but they are close to the lowest.

2023-08-19 to the present; blue for Fraser, red for VCH, green for Richmond.

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sarcozona

58 minutes ago

Timing for Covid vaccines is almost maximally bad in BC - a month after peak!

Epiphyte City

MAID increases — Ottawa holds firm by Meagan Gillmore
Friday December 5^th, 2025 at 11:46 PM

Canadian Affairs

Read: 5 min

The government of Canada has no plans to stop allowing medical assistance in dying (MAID) for people without reasonably foreseeable deaths, Health Canada told Canadian Affairs this week.

Health Canada’s response comes after the Nov. 28 release of its annual report about MAID deaths in Canada.

The report says there were 16,499 MAID deaths in 2024, accounting for five per cent of all deaths in Canada that year.

“MAID is no longer this exceptional procedure to facilitate the dying process,” said Trudo Lemmens, a law professor at the University of Toronto who has studied MAID extensively.

In 2024, most MAID deaths — nearly 96 per cent — involved cases where the patients were suffering and had serious and incurable illnesses, diseases or disabilities that would lead to reasonably foreseeable deaths. This is known as Track 1 MAID.

The other deaths — of 732 individuals — involved cases where people were suffering and had incurable diseases, illnesses or disabilities but did not have reasonably foreseeable deaths. This is known as Track 2 MAID.

Human rights experts have said Track 2 MAID makes it easier for people with disabilities to die than live and violates international human rights laws.

In March, the United Nations told Canada to stop Track 2 MAID, and to not expand eligibility for it further, including a planned 2027 expansion to people whose only medical condition is a mental illness.

The federal government told Canadian Affairs it has no plans to stop Track 2 MAID.

“The government of Canada is not currently planning to repeal Track 2,” a Health Canada spokesperson said in a Dec. 3 emailed statement.

Data concerns

Since MAID was legalized in 2016, more than 76,000 Canadians have died by MAID, with the number of deaths increasing each year.

However, Health Canada’s report notes the annual rate of increase is declining. There were about seven per cent more MAID deaths in 2024 than in 2023, whereas the rate increased by more than 30 per cent each year between 2019 and 2021.

“While the data suggests that the number of annual MAID provisions is beginning to stabilize, it will take several more years before long-term trends can be conclusively identified,” Health Canada’s report says.

The number of Track 2 MAID deaths increased by 17 per cent in 2024, the report adds.

“Seventeen per cent [increase] is not stabilized,” said Krista Carr, CEO of Inclusion Canada, an organization that works with people with developmental disabilities.

MAID patients can voluntarily report if they have a disability. According to the report, 31 per cent of Track 1 MAID patients and 61.5 per cent of Track 2 patients said they did.

However, not everyone who has a disability will say they have one, says Lemmens, of the University of Toronto. People who have recently acquired disabilities or have disabilities because of aging may not consider themselves disabled, he says.

According to definitions of disability in human rights laws, everyone who qualifies for Track 2 MAID has a disability, says Carr from Inclusion Canada.

“One hundred per cent of Track 2 recipients had a disability,” she said.

Health Canada’s report also said most MAID patients live in higher-income neighbourhoods. However, Track 2 patients are slightly more likely than the rest of Canadians to live in lower-income neighbourhoods.

Helen Long, the CEO of Dying With Dignity Canada, a charity that advocates for MAID access, says this shows MAID does not disproportionately impact vulnerable people.

“At a high level, people across Canada who receive MAID do not disproportionately come from lower-income or disadvantaged communities,” Long said in an emailed statement.

But some say Health Canada does not collect adequate data to determine if MAID patients are socially disadvantaged.

Postal code data “does not actually tell you what suffering that person in front of us is seeking MAID for,” said Dr. Sonu Gaind, a psychiatry professor at the University of Toronto.

Doctors should ask patients if poverty is prompting their requests for MAID, he says.

“We’re not collecting the data we need,” he said.

‘Meaningful opportunities’

The Health Canada report lists MAID patients’ self-reported causes of suffering. Doctors ask MAID patients about specific causes of suffering, and patients can report more than one cause.

For both Track 1 and Track 2 patients, the most frequently reported causes of suffering were the loss of the ability to engage in meaningful activities and to perform tasks of daily living. Loss of independence and loss of dignity were the third and fourth most common causes of suffering.

As in past years, most MAID patients were seniors.

Dr. Marnin Heisel, a clinical psychologist who specializes in seniors’ mental health, said seniors commonly report feeling like they do not “fit in with society.”

Heisel runs groups with retired men, helping them find meaningful activities. His research has shown that seniors who report high levels of meaning in life are less depressed and have fewer thoughts of suicide.

“We need to provide meaningful opportunities for people who are facing serious or life-threatening conditions,” he said.

Concerns about loneliness

Loneliness was cited as a factor in nearly 22 per cent of all Track 1 cases. That number rose to 44 per cent for Track 2 patients. Similar numbers were reported in Health Canada’s 2023 report.

In this year’s report, Health Canada noted that many have raised concerns about loneliness being a factor in MAID deaths. It referenced a December 2024 Canadian Affairs article about the topic.

In response to these concerns, Health Canada conducted a further analysis of data about loneliness among MAID patients.

It found that, in 2024, MAID patients who cited loneliness as a cause of suffering had more causes of suffering than people who did not list loneliness. But no one listed loneliness as their only source of suffering, the report says.

The report also says that people with chronic or lifelong medical conditions are more likely to experience loneliness.

Some experts caution that the report downplays concerns about loneliness influencing people’s requests for MAID.

The fact that people with chronic conditions are more likely to experience loneliness “doesn’t diminish the fact that people say that [loneliness is] a source of their intolerable suffering that leads them to have MAID,” Lemmens said.

“It’s a serious finding.”

Emotional distress

The report also shows a significant increase in the number of MAID patients suffering from emotional distress.

In 2024, nearly 58 per cent of Track 1 patients listed emotional distress, up from about 39 per cent the year before.

Meanwhile, 63 per cent of Track 2 patients listed emotional distress, up from 35 per cent the year before.

This may show an increase of people with mental illnesses and physical illnesses and disabilities requesting MAID, says Gaind, the psychiatry professor.

But “it could reflect a normalization of what people think it’s OK and suitable to have MAID for,” he said.

The increase in MAID patients reporting emotional distress could mean MAID assessors are focusing more on that during assessments, says Lemmens.

“[MAID] has become a [way] to address broader struggling,” he said.

“We have to ask ourselves whether that’s a healthy and a safe thing — that in our society, we say the appropriate way to deal with that is ending [someone’s] life.”

The post MAID increases — Ottawa holds firm appeared first on Canadian Affairs.

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sarcozona

1 hour ago

5% is a terrifying number

Epiphyte City

The Mighty Fitz
Friday December 5^th, 2025 at 11:25 PM

[Untitled]

“The lake [Superior] is huge and cold and blue and treacherous. It can sink freighters, drown people. In a wind the waves roll in with the crash of oceans.” Margaret Atwood, Cat’s Eye

Approximately 30 hours before I was born – a little after midnight on the 12^th of November 1975 – the Edmund Fitzgerald disappeared into the frigid depths of Lake Superior during a vicious winter storm. As rescue craft and nearby ships frantically scoured the tumultuous water surrounding the ship’s last known position, 750 miles southeast, at Mount Sinai Hospital, I was drawing my first keening breaths in this world. It’s almost certain the same Toronto newspaper that published my birth announcement (such things were done back then) also carried news of the tragedy somewhere in its front pages.

It’s thanks in large measure to Gordon Lightfoot’s song that the story is so well known, but here are some facts for the uninitiated:

• The Edmund Fitzgerald, or the Fitz as it was affectionately nicknamed, was launched in 1958, a bulk carrier (a ship that carries loose cargo which is loaded directly into its holds) built for the ore trade.

• At 729 feet it was the largest ship trading on the lakes and would remain such until the early 70s when the first 1000 footers, or ‘footers’ as they are known to those in the industry, were introduced.

• The Fitzgerald transported iron ore from the twin harbors of Duluth, Minnesota and Superior, Wisconsin on Lake Superior, down south to Detroit, Toledo and Cleveland where it was made into steel.

• In 1968, the Fitzgerald set a record for being the first ship to transport 29000 tons of taconite pellets through the Soo Locks (taconite pellets are iron ore balls, roughly the size of a marble, made from taconite rock; to be used in steel making) A month later it broke its own record with a load of 30000 tons.

By all accounts November 9^th, 1975, was a beautiful day in Duluth, the kind of day you might go golfing, one commentator on the tragedy remarked, and that’s saying something for Minnesota in November. When the Edmund Fitzgerald departed the Twin Harbors in the early afternoon, gale force winds and temperatures near freezing had been predicted for parts of Lake Superior. Unremarkable for the time of year or for a veteran captain like Ernest M. McSorley, 63, the master of the ship and one of the most respected skippers on the lakes. This was to be his final voyage before retiring. The Fitz was followed by another ore carrier, the Arthur M. Anderson, captained by Bernie Cooper. The captains knew of the storm brewing, the forecast had said as much and obvious atmospheric tell-tales would have spoken to this but by the next morning it became clear the storm had been greatly underestimated. The captains plotted the northern route around Superior – a storm route- hoping to catch some respite from the waves in the lee of the Canadian shoreline. What the Weather Bureau got wrong (they often got it wrong back then) and what the captains weren’t anticipating, was a storm of such magnitude. By the afternoon of the 10^th, conditions had deteriorated dangerously. Winds gusted to 85 knots – well over hurricane force – and with them came blizzards and unusually large waves – the worst Captain McSorley had ever seen, according to one of his radio transmissions.

We know now, from information relayed to Captain Cooper, that aboard the Fitz things were getting desperate. Two ballast tank vent covers on the main deck had been destroyed and the ship was listing – a sign she was taking on water. Worse yet, both of the Fitzgerald’s radars had been lost and McSorley was relying on the Anderson for positional reports.

“DON’T LET NOBODY ON DECK!” McSorley was heard to bark at one of his crew during a radio exchange with the Anderson.

Cooper and his officers monitored the progress of the stricken vessel on his radar. The Fitzgerald would have appeared as a green blip, or dot, on the screen. At times the dot would disappear because of interference from the incredibly high seas. The situation was alarming but there was safe water 17 miles ahead, Whitefish Bay, just over an hours steam away.

It would have been dark in the Anderson’s wheelhouse (it always is on a ship’s bridge as this improves your night vision) but a storm like that would have rendered it darker still. In blizzard conditions there is virtually zero visibility from the wheelhouse windows. Cooper was concerned the Fitz might be passing too close to Six Fathom Shoal, a reef located at the tip of Caribou Island on Superior’s eastern shore. Sometime around 7pm Cooper enquired as to the Fitzgerald’s condition and McSorley delivered the now infamous words,

‘We are holding our own.’

Moments later the green dot on the Anderson’s radar screen disappeared. This time it did not reappear.

I’d like you to think a moment on the senses. To consider what a Great Lakes sailor might see, hear and feel in conditions like the one’s these ships experienced. In white out conditions, in a gale on Lake Superior you simply don’t see anything, besides, at night, in a storm there would be nothing to see save for the running lights on the ship’s quarter catching the white froth of the turbulent seas. Ahead, the lake is black and the sky is black and they are as one. You might glimpse lights from distant ships and the shore. Looking out the wheelhouse windows in daylight hours, you would see something like the white static on an old TV when the reception went out or programming had finished for the night. As for sound, it is cacophonous. The shriek of the wind alone is deafening. Add to that the creaking of the long vessel as her hull works, bent to and fro by the tremendous seas. Particularly big waves cause a long ship to shudder from bow to stern, a horrifying feeling that can sink even the sturdiest greenhorn’s heart. The hatch covers wail and scream in protest as the deck flexes beneath them. There might be endless banging from heavy objects improperly secured and the ceaseless pounding of waves on the hull. Out on deck, in freezing conditions in a storm it’s easy to believe that there is a malevolent force at work in the universe, one that wishes you and your vessel harm. Remember, your senses are already heightened by the unrelenting clamor. And then there is the wind that wants to suck the breath from your mouth and flatten you to boot. In this it is abetted by an icy steel deck that renders every step treacherous. Any exposed skin – your wrists, your face – is flayed painfully by the wind. The snow comes at you with the velocity of BB pellets. Stings your cheeks. Blinds you.

A few years ago, my ship was making the same storm route around Lake Superior, beating a course to Thunder Bay. It was a pitch-dark night and the ship lurched unnaturally in the strengthening seas. The wind was a steady fifty, gusting to sixty and higher. Five miles behind us was the S_______. At some point, the wind carried away her anemometer. For the rest of the voyage they had to rely on us to relay the wind speed for their hourly logs.

Past crew members of the Fitzgerald have claimed that the hull moved or ‘worked’ more than most ships. (Remember that large ships, like skyscrapers are made to move, to bend and flex according to the conditions and their cargo.) They said that when they used the side tunnels (the tunnels that run the length of the deck, below the cargo holds) in bad seas, the watertight door at the end wasn’t even visible, such was the corkscrewing of the hull. This might sound familiar to some of my readers, as I had the same experience on another vessel in our fleet, also an ore carrier. For years I heard colleagues and people who’d sailed on her say ‘One day that ships going to break in two…’ and sure enough, at the beginning of last year’s season a 12-foot fissure suddenly opened up amidship in the middle of Lake Superior. Help came quickly and the crew were evacuated safely but if the weather hadn’t been as good as it was the outcome would have been very different. The ship sits in permanent (?) layup in Superior,Wisconsin.

Seven days before the Edmund Fitzgerald sank, she was audited by her insurers. There were found to be discrepancies on hatches 13, 15, 16 and 21. This is not uncommon. These are hardworking ships and the hatch covers and combings take a beating. Four vents on deck were also found to be deficient. The Fitzgerald was permitted one more trip after which the repairs had to be made. Two months ago, delivering grain to Quebec City, a piloting error caused the M_______ to run aground in the St. Lawrence seaway. We managed to tie her up safely within an hour of the incident, but it became clear that significant damage had been done as the ship flopped over with a two-meter list. 15 punctures in all were discovered, ranging in size from a few inches to over six feet long. The reef had made a colander of us. The next two weeks were spent on the wall at Iroquois Lock as teams of divers and welders worked around the clock to seal her up. The process involved a diver placing a temporary patch on the outside of the hull over the hole. Welders went down into the ballast tanks to build ‘coffer dams’ or cement boxes. This entails welding a metal box around the hole, filling it with cement, and finally, welding a lid on it. No small task in a confined space when you’re dealing with a man-sized rend in the ship. When the repairs were completed, an audit was conducted by our insurers who gave us the all clear to proceed. We were given a dispensation to finish the season on the provision that the M_____ dry dock in the winter and do the sizable repairs. When we’re underway carrying cargo and the ballast tanks are empty, wheelsman must do soundings every four hours, to make sure the patches are holding. In the rough winter weather when the hull works extra hard, and with the loading and unloading of cargo there is concern that the cement could crumble or a weld on a box could crack. Otherwise, life aboard continues much as it did before. I am not trying to draw some clumsy comparison of my ship’s misfortunes with the fate of the Fitz. I’m merely illustrating how commonplace sailing with deficiencies is. Time is money, and, in relative terms, the sailing season is short. If you were to investigate, I’m certain you would find dozens of ships operating on the lakes are sailing with some sort of dispensation and 99.9% of the time it’s alright. I sleep just as well as I did before we were holed and I’m sure all of my fellow crew do too. To use a phrase I seem to hear everywhere and absolutely loathe, it is what it is. That is, until it isn’t. And when it isn’t, on the Great Lakes, shit can go south in a hurry.

There is a childish notion – or at least a notion I possessed when a boy, being then, as I am now, ill-versed in the laws of physics – that when a ship goes down it does so gently, as a feather falling from a great height might, describing lazy parabolas as it glides down into the depths to nestle like a plump cat, ever more, on the seabed. This is obviously not the case. When a ship goes down, when it achieves negative buoyancy and passes beneath the surface, it goes down in a hurry, gaining speed the deeper it goes. When it hits bottom it does not ‘come to rest’ softly, it crashes with tremendous force – with the violence of falling buildings. We don’t know exactly what happened to the Edmund Fitzgerald, the firsthand witnesses, all 29 of them, went down with her. We do know that it must have happened quickly. So quick that the crew didn’t have time to launch life rafts or don life jackets (even with a life jacket on in that icy Superior water, you would have about five minutes before you lost consciousness. Within ten minutes you would be dead.) The wreck lies in 550 feet of water and is in two pieces. Did she split apart on the waves? This had happened 8 years before, to the Daniel J. Morrell, another bulk freighter of similar dimensions, that sank in a November storm on Huron. According to the sole survivor of the 29-man crew, when she split apart the bow section sank immediately while the stern section continued on under its own power. It would keep going for another five miles before finally succumbing to the waves. Or did the Fitz break in two after she sank? When she collided with the seabed. And if the Mighty Fitz didn’t split apart then what was it? Did she take on too much water? Founder in those awful seas? Did she hit bottom on six fathom shoal causing catastrophic damage to her hull? Cooper reported that the Anderson was struck by three enormous waves in quick succession shortly before the Fitz disappeared from the radar screen. Was it these that were her undoing? The fabled three sisters of the Great Lakes come to claim her.

The current captain of the M________ was the 2nd mate on the Hilda Marjanne on the night the Fitz went down. They were sheltering in Whitefish Bay when the emergency call went out so the anchor was weighed and they headed out into the open lake. The conditions were awful and there was zero visibility in the wheelhouse. The wheelsman was violently ill and vomited profusely as he struggled to steer a straight course while the ship bucked and rolled in the seas. When the wind blew in three of the windows on the bridge, effectively letting the storm inside, the captain was forced to abandon the search and they turned back for the shelter of the bay. In the course of the turn the steam powered ship rolled severely, knocking one of her boilers and the turbine it powered off line. Chastened, the ship limped back to safety.

Seven years ago, just before Christmas, I had a near miss on the ship I was working on. While I have alluded to the incident in some of my dispatches, I’ve resisted writing about the experience directly for reasons I’m still unsure of. Surely, for a writer of the nautical experience, being thrown from a punt into the icy water and nearly copping it in the freezing water of the St. Marys River, a few miles from Whitefish Bay, the same safe water the Fitz never made it to, surely that would be great fodder for the page. Surely that would be the ‘gold’ Joan Didion once referred to in a documentary on her life. But I haven’t and perhaps that is for a therapist to unpack. I don’t believe I was, or am, unduly traumatized by the incident, though people said I would be. Occasionally, I have the odd bad dream and wake with a start, but I am and have always been an inveterate dreamer of bad dreams and what’s more, my near miss, that five minutes I spent in the water is trivial when compared to the suffering people less lucky than me have endured. Of course, the incident cost most of the hearing in my left ear, which, to be sure, is a bit of a bugger but seems piddling when compared to the unspeakable traumas many people around the world incur daily. On the whole, I’ve been content to describe the humdrum day-to-day life of a Great Lakes Sailor, the stultifying routine and yes, the odd bouts of excitement. And then there is the great beauty of the natural world that I am often privy to. I have been careful not to romanticize my experiences either, but I will say this about my accident – as I bobbed there in the river, pulled one way by the rivers current and another by the life ring and rope tethering me to the ship and after those first exploratory tendrils of icy cold water permeated my thick winter layers and then, quickly engulfed me and my boots filled and became so heavy it felt as though ghoulish hands had me by the ankles and were trying to pull me under and were only prevented from doing so by my life jacket, which for some reason that day I had chosen to zip up correctly rather than wear it loose as I had done all season – as I got colder and my senses dulled, my initial terror subsided and instead was replaced by a kind of stunned reticence, it felt like a dimmer switch was being slowly dialed down on my consciousness and I was content to let it. But I do remember, despite this brain fog, distinctly thinking three things. First of all, how sorry I was that my parents were going to receive a terrible phone call on Christmas eve of all days. Secondly, how bummed I was that I would not be finishing Olivia Manning’s Fortunes of War trilogy, which at that point I was halfway through. And thirdly, and so unfair and absurd was this notion that I actually remember chuckling to myself, I thought, are you fucking kidding me? All the stupid shit I have done in my life and this is how I’m going to go out? For work! For my job! For a pay cheque? It struck me as a rip off. Who knows what thoughts exist in the secret minds of men? When the jig is up and the clock is running out. I know what mine were, and they were startling in their banality. The men on the Fitzgerald, they weren’t heroes. They were just doing their jobs too. Fathers, husbands, brothers, sons, cousins, uncles, friends. A lot like the men (and occasional women) I sail with here. Folks who choose to spend half the year away from their loved ones, to miss out on birthdays, Christmases, first steps and graduations, to afford a better life for their families. A life they could not easily furnish with wages earned ashore. Thankfully, my parents did not receive a phone call. The company made me sign a wager absolving them of any responsibility in the accident while I was still dripping wet, but I got to go home for Christmas.

The Edmund Fitzgerald was the last modern freighter to sink on the lakes. There were no survivors of the tragedy and not a single body has ever been recovered. As Gordon Lightfoot sings the lake ‘never gives up its dead.’ This is no fabulist’s claim. Because the water is so cold year round in Superior, the decomposition process that causes a body to resurface is hampered, therefore when you drown, you stay down, your body preserved. The tragedy caused a change in safety standards industry-wide. Better life rafts with hydrostatic releases were introduced as well as the issue of an immersion suit to every man on board. Weather forecasts are much more reliable these days too. With an app on my phone I’m able to get a good idea of what the wind speed and wave height will be like anywhere in the world right now and in the days to come.

For the past week we have been hammered by November storms. Much of this essay was written at anchor off Long Point in Lake Erie, where we sought refuge along with nine other ships. For 48 hours the wind did not drop below 30 knots and regularly gusted to 50. As I sat typing in my cabin I could hear the wind rage, rattling the super structure around me. Sleet and snow frenzied at my cabin window. At times the ship strained against the anchor chain and sent judders through the hull which I could feel 600 feet aft at my desk. Despite being in the lee of Long Point, the waves were tall and relentless. For 24 hours there was not a single ship moving across the entirety of the Great Lakes. Currently we’re storm routing up the American side of Lake Huron and we anticipate many more weather related delays before the season is done. Winter has arrived and this year her claws are out.

November 10^th marked the 50^th anniversary of the loss of the Edmund Fitzgerald and two days later, I turned 50. I was in the UK on the day of my birthday, and in the morning I went for a run in Victoria Park with my girlfriend’s dog, a black working cocker named Sissy. The dirt path was strewn with leaves and the air was brisk and there was the pleasing smell of wood smoke coming from the chimneys of the long boats on the canal. Occasionally Sissy would take off at great speed to tree a grey squirrel, kicking up an exhaust of red and yellow leaves as she did so, or she’d stop to roll ecstatically in something foul but for the most part, we ran side by side. I found myself looking down at her from time to time, and marveling at this creature, her glistening pelt, her effortless gait. Sometimes she would glance up at me. ‘What a good girl,’ I told her, because she was. I felt a fluttering in my chest, a spreading warmth, because she looked so pleased, so happy and I was as surprised as anyone to realize then, that I was happy too.

50 is, to me, a hell of a number and turning it has taken some processing. Have I valuable insights to offer the youth from my lofty vantage? Not really. Try and be kind and make your bed are about the best words of advice I feel qualified to proffer. Oh, and read more. Most of the men on the Fitzgerald never got this chance. These years. I think of them often, especially around my birthday. What they may have gone through and their thoughts in those final, awful minutes and seconds. As all 29 of them were leaving this place, I was just arriving, so close they might have held open the door.

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sarcozona

1 hour ago

This is very good.

Epiphyte City

Trump admin may deny H-1B visas to people who worked in content moderation, report says | The Verge
Friday December 5^th, 2025 at 10:01 PM

The Verge

The Trump administration has ordered US consulates to consider rejecting H-1B visa applicants involved in content moderation or “censorship,” according to a report from Reuters. A State Department cable viewed by the outlet says officials should check an applicant’s resume or LinkedIn profile for a job history involving moderation, fact-checking, online safety, compliance, and misinformation.

As reported by Reuters, the cable says the policy applies to all visa applicants, but it’s directed at people applying for an H-1B visa who may have had a history of working in “social media or financial services companies involved in the suppression of protected expression.” Many tech companies, such as Amazon, Google, and Microsoft, hire highly skilled workers on H-1B visas.

“If you uncover evidence an applicant was responsible for, or complicit in, censorship or attempted censorship of protected expression in the United States, you should pursue a finding that the applicant is ineligible,” the cable says, according to Reuters. “You must thoroughly explore their employment histories to ensure no participation in such activities.”

President Donald Trump began tightening immigration policies earlier this year, instructing the State Department to screen the social media accounts of student visa applicants and later requiring a $100,000 fee alongside H-1B visa applications. Trump has since paused immigration applications from 19 “countries of concern” following the National Guard shooting in Washington, DC.

“People who study misinformation and work on content-moderation teams aren’t engaged in ‘censorship’ — they’re engaged in activities that the First Amendment was designed to protect,” Carrie DeCell, the senior staff attorney and legislative advisor at the Knight First Amendment Institute at Columbia University, says in a statement. “This policy is incoherent and unconstitutional.”

When asked about its new immigration vetting process, a State Department spokesperson told Reuters that the agency doesn’t comment on “allegedly leaked documents” but added that “we do not support aliens coming to the United States to work as censors muzzling Americans.” The State Department didn’t immediately respond to The Verge’s request for comment.

Correction, December 4th: Corrected mention of “H1-B” visa to “H-1B.”

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sarcozona

3 hours ago

America is going to ban people who kept snuff films and kiddie porn out of their feeds. Cool.

Epiphyte City

Distinct brain alterations and neurodegenerative processes in cognitive impairment associated with post-acute sequelae of COVID-19 | Nature Communications
Friday December 5^th, 2025 at 4:05 PM

Nature Communications

Distinct brain alterations and neurodegenerative processes in cognitive impairment associated with post-acute sequelae of COVID-19

Article
Open access
Published:

Nature Communications 16, Article number: 10552 (2025) Cite this article

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Although brain alterations have been reported in post-acute sequelae of SARS-CoV-2 (PASC), their prevalence and relationship to neurodegeneration remain unclear. We analyzed blood proteins and brain MRI from individuals approximately one year after mild COVID-19, categorized as Cog-PASC (with cognitive impairment), Other-PASC (without cognitive impairment), or non-PASC controls, across exploration, covariate-matched, and independent validation cohorts. In the exploration cohort, Cog-PASC showed elevated astroglial damage–associated proteins and structural and microstructural alterations across multiple cortical and subcortical regions, including cortical thinning in the cingulate and insular cortices, increased paramagnetic susceptibility in the hippocampus, and enlarged choroid plexus volume. In the age-, sex-, and education–matched cohort, cortical thinning and increased susceptibility in the cingulate remained significant. Blood proteomics revealed broader alterations involving oxidative stress responses and synaptic function in Cog-PASC, linked to neurodegenerative pathways. In the validation cohort, increased neuronal and astroglial damage-associated proteins, cortical thinning in the cingulate and insular cortices, and increased hippocampal susceptibility were demonstrated, along with enlarged choroid plexus, confirming the reproducibility of these neurodegeneration-associated alterations. These findings suggest distinct neurodegenerative processes in Cog-PASC not observed in other-PASC subtypes, even after mild COVID-19 infection.

Article Open access 03 March 2022

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), now endemic, causes long coronavirus disease (COVID) or post-acute sequelae of SARS-CoV-2 infection (PASC), which has become a significant healthcare burden¹. Long COVID presents with various symptoms, including respiratory, neurological, cardiovascular, gastrointestinal, musculoskeletal, and psychological issues that can persist for >1 year in both hospitalized and non-hospitalized patients¹. Its pathogenesis likely involves multiple mechanisms¹, including tissue damage, viral reservoirs, autoimmunity, and persistent complement-mediated immunopathology associated with thromboinflammation^2,3,4.

Brain alterations may occur after COVID-19 infection^5,6,7,8,9,10. A UK Biobank magnetic resonance imaging (MRI) study revealed increased diffusion indices in the limbic regions and striatum and reduced cortical thickness in the orbitofrontal and parahippocampal areas, regardless of cognitive dysfunction⁵. Recent imaging studies have indicated distinct microstructural changes in long COVID^6,7, with network disruptions varying by symptom type, such as cognitive impairment, olfactory dysfunction, and fatigue^7,9. Brain changes may be more pronounced in individuals with cognitive impairment, marked by blood-brain barrier (BBB) disruption⁸, elevated brain injury markers⁹, and reduced gray matter volume¹⁰, even 1 year after the infection. However, whether these brain changes represent previous injury or are accompanied by ongoing neurodegenerative processes, as well as whether such processes are universal across PASC patients, particularly in individuals who experienced mild COVID-19, is unclear.

Advanced magnetic resonance imaging techniques may offer insights into neurodegeneration following SARS-CoV-2 infection beyond gray matter measurements. Iron, which is crucial for metabolism, myelin synthesis, and neurotransmitter production, can contribute to neurodegeneration when accumulated excessively¹¹. Paramagnetic susceptibility MRI assesses brain iron levels by detecting faster T2*-weighted signal decay¹², with increased iron deposition observed in conditions such as Alzheimer’s disease (AD)¹³. The choroid plexus (CP), forming the blood–CSF barrier and producing CSF, plays a role in waste clearance and regulates immune cell entry¹⁴. Blood–CSF barrier disruption may impair clearance, contributing to neuroinflammation and neurodegeneration⁸. Structural changes in the CP, such as enlargement, were observed in neurodegenerative diseases^15,16. The glymphatic system, responsible for clearing brain waste via cerebrospinal fluid (CSF), can be disrupted by neuroinflammation, leading to abnormal protein aggregation—a hallmark of neurodegeneration¹⁷. Diffusion tensor imaging analysis along the perivascular space (DTI-ALPS), which measures radial water diffusion at the lateral ventricles, shows reduced indices when glymphatic function is impaired, as observed in various neurodegenerative diseases^18,19. In addition to ALPS indices, other DTI-derived metrics such as mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA) can provide complementary insights: increased MD reflects overall microstructural damage and increased water diffusivity, elevated RD is often associated with demyelination, and reduced FA indicates loss of axonal integrity and fiber organization²⁰. Brain imaging studies assessing iron deposition, CP alterations, and these DTI parameters may help delineate neurodegenerative processes in the brain after SARS-CoV-2 infection.

Ultrasensitive or high-throughput protein analysis can offer a crucial understanding of the pathogenesis of long-COVID cognitive impairment. Neurons and glial cells release essential proteins, which can be drained into the CSF via the glymphatic system and subsequently into systemic circulation, even without blood-brain barrier disruption²¹. This release increases with brain damage, especially with BBB damage, offering clues about the extent of damage and ongoing pathology. For instance, elevated neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) levels reflect neuronal and astroglial damage^22,23,24, while the altered Aβ42/Aβ40 ratio and increased phosphorylated tau levels suggest AD pathology^25,26. In addition to brain-specific proteins, blood contains markers of systemic inflammation and metabolism. While previous studies on long-COVID cognitive impairment identified unique proteomic signatures, they mainly focused on inflammatory and vascular proteins^27,28,29,30. A more comprehensive proteomic analysis, incorporating diverse biological pathways, could offer deeper insights into the mechanisms underlying the changes in long-COVID.

Therefore, we employed advanced brain MRI and high-throughput proteomics in individuals at least 3 months after COVID-19 (mainly 1 year after COVID-19), with mostly non-hospitalized mild COVID-19. Participants were grouped into three categories: PASC with cognitive impairment (Cog-PASC), PASC without cognitive impairment (Other-PASC), and no significant PASC (NS-PASC). We hypothesized that cognitive dysfunction in long COVID would show distinct neurodegenerative changes. To investigate this, we analyzed cross-sectional data from the LOCOMOTIVE study (LOng Covid Outcome MOnitoring with Translational InVEstigations of blood and neuroimaging; cris.nih.go.kr, KCT0007848), an ongoing prospective, longitudinal study of long COVID. In the exploration cohort, the Cog-PASC group showed elevated astroglial damage-associated proteins, cortical thinning in the cingulate and insular cortices, increased paramagnetic susceptibility in the hippocampus, and enlarged choroid plexus volume. In a covariate-matched cohort based on age, sex, and education, cortical thinning and susceptibility in the cingulate persisted. Proteomic profiling revealed additional alterations in oxidative stress responses and synaptic function, consistent with neurodegenerative pathways. In the independent validation cohort, elevations in neuronal and astroglial damage-associated proteins, cortical thinning in the cingulate and insular cortices, and increased hippocampal susceptibility were reproduced, confirming the robustness of these alterations. Together, these findings suggest unique neurodegenerative processes in Cog-PASC not prominent in other-PASC patients even after mild COVID-19.

The LOCOMOTIVE cohort consists of two independent groups, the exploration and validation cohorts, divided according to enrollment dates (Fig. 1a). In this preliminary cross-sectional study, participants with confirmed COVID-19 and positive SARS-CoV-2 antibody tests were classified into three groups: Cog-PASC (with cognitive impairment), Other-PASC (without cognitive impairment but with other-PASC symptoms), and no significant PASC (NS-PASC). Brain MRI and blood biomarker assessments were conducted in the exploration cohort, with confirmatory analyses performed in the validation cohort.

Fig. 1: Exploration cohort overview: study design and neurologic sequelae across PASC subgroups.

a A total of 278 individuals were enrolled between November 2022 and April 2025, of whom 269 with prior COVID-19 infection were included in the present analysis after excluding nine uninfected participants. All participants underwent cognitive evaluations using the Montreal Cognitive Assessment (MoCA), the Fatigue Assessment Scale (FAS), and a symptom-based Post-Acute Sequelae of COVID-19 (PASC) questionnaire designed to assess cognitive impairment. Based on the time of enrollment, participants were assigned to the exploration cohort (n = 160; November 2022–October 2023) and the validation cohort (n = 109; November 2023–April 2025). Each cohort was further stratified into three clinical subgroups according to symptom profiles: NS-PASC (exploration: n = 77, validation: n = 46), Other-PASC (exploration: n = 55, validation: n = 47), and Cog-PASC (exploration: n = 28, validation: n = 16). The study encompassed three main analytical approaches: PASC symptom questionnaires for cognitive function assessment (including 32 symptoms covering brain fog, fatigue, sleep disturbances, dizziness, headache, myalgia, and anxiety/depression), blood analysis using proteomic techniques (Proximity Extension Assay [PEA] with Olink 3072 Explore platform and Single-Molecule Array [Simoa] measuring GFAP, NfL, Aβ42/40 ratio, p-Tau181), and brain Magnetic Resonance Imaging (MRI) analysis focusing on cortical parcellation, paramagnetic susceptibility maps, choroid plexus segmentation, and DTI-ALPS processing. b, c Comparison of long COVID-related neurologic symptoms between NS-PASC vs. PASC and Other-PASC vs. Cog-PASC subgroups. Two-sided Pearson’s Chi-square tests were used to analyze categorical variables. Significance levels are indicated as *p < 0.05, **p < 0.01, and ***p < 0.001. χ² statistics, degrees of freedom, and exact p-values are provided in the Source Data file.

In the exploration cohort, 169 participants were prospectively recruited, of whom 160 were included in the analysis. Among the included patients, 28 individuals were classified as Cog-PASC, 55 as Other-PASC, and 77 as NS-PASC (Table 1). Of these, 107/160 (66.9%) were female. Participants were enrolled a median of 12.0 months after infection [IQR 7.0–14.0], and MRI was performed at a median of 13.0 months [IQR 8.0–15.0] post-infection, with no significant differences among groups. Most participants had been infected during the Omicron-dominant period.

Table 1 Baseline characteristics of the participants in the exploration cohort

The Cog-PASC group was older and had a higher proportion of females than the NS-PASC group but fewer females than the Other-PASC group (Table 1). Participants in the Cog-PASC group also had the fewest years of education. Given the unequal distribution of age, sex, and education across groups, these variables were adjusted for in all subsequent comparative analyses. Most participants experienced mild COVID-19 infections, not requiring hospitalization. The Cog-PASC group had significantly lower Montreal Cognitive Assessment (MoCA) scores than the Other-PASC and NS-PASC groups, with a median MoCA score of 24. Meanwhile, Fatigue Assessment Scale (FAS) scores, indicating more severe fatigue with higher values, were higher in the Other-PASC group compared to the Cog-PASC group. However, PASC scores were similar between the two groups, both showing mild symptoms (median score: 11, with a significant symptom threshold of 12). Symptom prevalence was higher in both Cog-PASC and Other-PASC groups compared to NS-PASC, with similar symptom patterns between the two PASC groups except for more frequent post-exertional malaise in Other-PASC (Fig. 1b, c). Notably, brain fog was reported at comparable rates between the two groups, aligning with previous findings that self-reported brain fog does not reliably reflect objective cognitive impairment³¹. These findings suggest that individuals with Cog-PASC also experienced other-PASC symptoms at levels generally similar to those in the Other-PASC group.

The Cog-PASC group shows brain damage and neurodegenerative changes

We analyzed blood samples to investigate potential brain damage in the Cog-PASC group using ultrasensitive single-molecule array (Simoa) technology to measure biomarkers of astroglial (GFAP) and neuronal (NfL) damage^23,24, as well as AD-related markers such as β-amyloid (Aβ42/Aβ40 ratios) and tau (p-Tau181)^25,26. The Cog-PASC group exhibited significantly higher GFAP levels than the other groups but comparable levels of the NfL, Aβ42/Aβ40 ratio, and p-Tau181 (Fig. 2a–d). GFAP and NfL were significantly correlated with cognitive dysfunction, as measured by MoCA scores, while AD-related biomarkers were not; however, these correlations became non-significant after adjusting for age, sex, and education (Supplementary Fig. 1a–d). Notably, neither GFAP nor NfL correlated with fatigue (FAS scores) or other long-COVID symptoms (PASC scores), even in unadjusted analyses, suggesting a more specific association with cognitive function than with general PASC symptoms (Supplementary Fig. 1e–h).

Fig. 2: Brain injury biomarkers and neurostructural MRI metrics in the exploration cohort.

a–d Levels of Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light Chain (NfL), Amyloid-beta 42/40 ratio (Aβ42/40 ratio), and phosphorylated tau 181 (p-Tau181) were compared among the subgroups within the exploration cohort: NS-PASC (n = 77), Other-PASC (n = 55), and Cog-PASC (n = 28). e Mean cortical thickness was measured from 3D T1-weighted MRI using the FreeSurfer cortical parcellation tool (v.7.3). Iron deposition was assessed by susceptibility source separation of multiecho gradient echo images into paramagnetic susceptibility maps. f Surface-based morphometry maps indicate regions with reduced cortical thickness in Cog-PASC patients. Red highlights show the cingulate (left) and insular cortex (right) across lateral, medial, and coronal views (top to bottom). g Box plot illustrating group-wise differences in cortical thickness (mm) across regions (NS-PASC (n = 77), Other-PASC (n = 55), and Cog-PASC (n = 28). h Standardized beta coefficients from multiple linear regression models assessing associations between MoCA scores and cortical thickness in the cingulate, parahippocampal, and insular cortex. i Group-wise comparison of paramagnetic susceptibility values (ppm) in the cingulate cortex. j Heat map of correlations (r) between cortical thickness and regional iron deposition. k Box plots of paramagnetic susceptibility (ppm) across cortical regions (NS-PASC (n = 39), Other-PASC (n = 29), and Cog-PASC (n = 12). l Standardized beta coefficients from regression models examining associations between MoCA scores and cortical iron deposition in the cingulate, occipital cortex, and hippocampus. m Choroid plexus segmentation from 3D T1-weighted MRI (left) and DTI-based ALPS index calculation (right). n Group-wise comparison of choroid plexus volume (CPV) fraction and DTI-ALPS index (NS-PASC (n = 39), Other-PASC (n = 29), and Cog-PASC (n = 12). o Standardized beta coefficients for associations of these metrics with MoCA scores. adjusted for age, sex, and education. Significance levels are indicated by asterisks: For all box plots, the center line indicates the median, box boundaries the interquartile range (IQR; 25th–75th percentiles), and whiskers extend to the most extreme data points within 1.5 × IQR. Data points beyond whiskers are shown as outliers. Group comparisons were performed using Two-sided ANCOVA, adjusting for age, sex, and education. Regression models were adjusted for the same covariates. All p-values were corrected for multiple comparisons using the false discovery rate (FDR); significance levels are indicated as *adjusted p < 0.05, **adjusted p < 0.01, and ***adjusted p < 0.001. Exact p-values are provided in the Source Data file.

We assessed cortical gray matter thickness and volume using automated MRI processing, including segmentation and surface-based morphometry (Fig. 2e, f). Cortical thickness was generally comparable across most regions, except for the cingulate, insular cortex, and parahippocampal gyrus, which were thinner in the Cog-PASC group compared to the Other-PASC group (Table 2 and Fig. 2g). Insular cortex thickness showed a significant association with total MoCA scores in regression analysis adjusted for age, sex, and education (Fig. 2h). Meanwhile, volumetric comparisons of cortical and subcortical regions showed no group differences (Table 2).

Table 2 Parameters of magnetic resonance imaging: thickness and paramagnetic susceptibility in the exploration cohort

We evaluated iron deposition in cortical and deep gray matter using the χ-separation method³², which maps paramagnetic susceptibility (Fig. 2e, i). Susceptibility was generally negatively correlated with cortical thickness, with a particularly significant association in the temporal cortex (Fig. 2j). The Cog-PASC group exhibited higher paramagnetic susceptibility, indicating increased iron deposition, in the cingulate and occipital cortices as well as the hippocampus (Table 2 and Fig. 2k). Among these regions, susceptibility in the occipital cortex and hippocampus was significantly associated with total MoCA scores (Fig. 2l). When we evaluated associations between these brain changes (whole cortical thickness or paramagnetic susceptibility) and fatigue or other long-COVID symptoms, no significant correlations were identified (Supplementary Fig. 2a–d).

Next, we assessed the CP volume fraction (CPV fraction) using segmentation of 3D T1-weighted images and evaluated various MRI parameters from diffusion tensor imaging (DTI), including the DTI-ALPS index (Fig. 2m). The CPV fraction was significantly higher in the Cog-PASC group than in the Other-PASC group. The DTI-ALPS index was lower in the Cog-PASC group, and Tract-Based Spatial Statistics (TBSS) demonstrated reduced FA with higher MD and RD in major white matter tracts. However, none of these differences reached statistical significance (Table 2, Fig. 2n, Supplementary Fig. 3a, b). Regression analyses revealed no significant associations between CPV fraction or DTI-ALPS index and MoCA scores (Fig. 2o), suggesting these brain measures may not directly reflect cognitive function. Similarly, neither metric revealed significant correlations with other symptom scores, including FAS and PASC scores (Supplementary Fig. 2e–h).

Collectively, these findings suggest that the Cog-PASC group exhibits evidence of brain injury and neurodegenerative changes, characterized by elevated astroglial damage markers, reduced cortical thickness, iron accumulation, and increased choroid plexus volume, without notable alterations in AD-related biomarkers.

Covariate matching confirms brain alterations in Cog-PASC

Due to significant differences in age, sex, and education among the PASC groups, we further conducted a covariate matching analysis to adjust for these variables. Participants were matched 1:1 using nearest-neighbor matching without replacement, based on logistic regression models that included age, sex, and education as covariates. Following matching, baseline characteristics were balanced across the PASC groups, with the exception of MoCA, FAS, and PASC scores (Table 3). The Cog-PASC group exhibited greater cognitive impairment, the Other-PASC group showed higher fatigue scores, and PASC scores remained comparable between groups, consistent with the original cohort findings (Table 1).

Table 3 Baseline characteristics of the participants in the covariate-matched cohort

In analyses of astroglial/neuronal injury and AD-related blood biomarkers, the Cog-PASC group showed a trend toward higher GFAP levels, although this did not reach statistical significance. No significant differences were observed in other blood biomarkers across groups (Supplementary Fig. 4a–d). Regarding brain MRI biomarkers, the Cog-PASC group demonstrated significantly thinner cortex and increased paramagnetic susceptibility in the cingulate cortex (Table 4). Similar trends toward increased paramagnetic susceptibility were observed in the occipital and insular cortices and hippocampus, though they did not achieve statistical significance. The CPV fraction and DTI-ALPS index did not significantly differ between groups.

Table 4 Parameters of magnetic resonance imaging: thickness and paramagnetic susceptibility in the covariate-matched cohort

Taken together, these findings suggest that evidence of brain damage and neurodegenerative changes on MRI persists even after covariate matching, replicating the results from the original group comparisons.

The Cog-PASC group has distinct blood proteomic signatures linked to neurodegeneration

To explore the mechanisms underlying Cog-PASC, we applied high-throughput Olink proteomics²⁹ to measure 3072 serum proteins. Although a principal component analysis was performed to differentiate the three groups, the separation was not distinct, except for the Cog-PASC group, which showed a non-overlapping region (Fig. 3a). No significant differences were observed between PASC (Cog-PASC and Other-PASC) and NS-PASC groups, reflecting the chronic and mild nature of PASC symptoms in this cohort (Supplementary Fig. 5a).

Fig. 3: Distinct proteomic signatures of Cog-PASC in the exploration cohort.

a Principal component analysis (PCA) of PASC groups, showing PCA1 (x-axis) vs. PCA2 (y-axis). b, c Volcano plot depicting differentially expressed proteins (DEPs), defined as those with |log₂ fold change | > 0.5 and Benjamini–Hochberg false discovery rate (FDR)-adjusted p < 0.05 (vertical and horizontal dashed lines). Effect sizes and p-values were obtained from multivariable linear regression of protein abundance on group (Cog-PASC vs. NS-PASC; Cog-PASC vs. Other-PASC), adjusting for age; p-values are two-sided. b Top five downregulated proteins (blue dots) and one upregulated protein (pink dot) are highlighted in Cog-PASC vs. NS-PASC. c No DEPs identified between Cog-PASC and Other-PASC. Multivariate linear regression, adjusting for age, was applied. d Bubble plots of enriched Gene Ontology (GO) biological processes based on DEPs between Cog-PASC and NS-PASC, with adjusted p-value < 0.05 for enrichment terms. e Bar plot representing significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways based on DEPs between Cog-PASC and NS-PASC. Pathways are ranked by adjusted p-value, with color intensity representing significance (adjusted p < 0.05). The x-axis shows the number of proteins involved in each pathway (count). f Protein–protein interaction (PPI) network of DEPs was constructed using the STRING database, with high centrality proteins (SOD1, STAMBP, MRI1, EIF4B). g Standardized beta coefficients from regression models examining associations between MoCA, FAS, and PASC scores and 44 differentially expressed proteins (DEPs). h Comparison of inflammatory and vascular markers^3,8,56 between NS-PASC and PASC groups (NS-PASC (n = 77), Other-PASC (n = 55), and Cog-PASC (n = 28). Box plots show the median (center line), 25th and 75th percentiles (bounds of box; interquartile range, IQR), and whiskers extending to the most extreme data points within 1.5×IQR. Data points beyond whiskers are shown as outliers. Fold change was calculated for each biomarker relative to the Non-PASC group median. i Standardized beta coefficients from multiple linear regression models examining associations between MoCA, FAS, and PASC scores and inflammatory and vascular markers, in (i), the colored annotation bar beneath the matrix indicates group-specific significance of each marker. j, k Cognitive impairment (CI) prediction using LASSO-based multivariable logistic regression. j ROC performance plot. k Standardized coefficient estimates for variables retained in the final model (ARHGAP1, CASQ2, TREM2). Bars represent mean logistic regression coefficient estimates (log odds), with error bars indicating ±1 standard error. Positive coefficients indicate increased odds of Cog-PASC, while negative coefficients indicate decreased odds. Sample sizes were NS-PASC (n = 77), Other-PASC (n = 55), and Cog-PASC (n = 28). All regression models were adjusted for age, sex, and education unless otherwise specified. p-values were corrected for multiple comparisons using the Benjamini–Hochberg false discovery rate (FDR). Significance levels: *adjusted p < 0.05, **adjusted p < 0.01, ***adjusted p < 0.001. Exact p-values are provided in the Source Data file.

Comparison between Cog-PASC and NS-PASC groups revealed 44 differentially expressed proteins (DEPs), including 43 downregulated DEPs and one upregulated DEP (Fig. 3b and Supplementary Table 1)^{33,34,35,36,37}. The downregulated DEPs were functionally linked to synaptic regulation and neurotransmission (e.g., WASF3, ARHGAP1, ADD1, EIF4B, SH3GLB2), oxidative stress response (SOD1, CCS), de-ubiquitination (YOD1, STAMBP), and apoptotic signaling (CRADD). The five most prominently downregulated proteins were WASF3, YOD1, ARHGAP1, CA2, and CRADD. CASQ2 was the only upregulated protein associated with calcium ion regulation. No significant protein expression differences were observed between the Cog-PASC and Other-PASC groups or between Other-PASC and NS-PASC groups (Fig. 3c and Supplementary Fig. 5b).

Gene Ontology (GO) analysis of the DEPs highlighted pathways related to oxidative stress and synaptic functions, while Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified neurodegeneration as the most significant pathway (Fig. 3d, e). Protein–protein interaction analysis revealed four main clusters centered on SOD1, STAMBP, MRI1, and EIF4B (Fig. 3f). MoCA scores were significantly associated with 24 of the 44 DEPs (54.5%) in regression analysis, whereas no associations were found with FAS or PASC scores (Fig. 3g), suggesting a specific relationship between these proteins and cognitive function.

Then, we examined various proteins, including immune and vascular regulatory proteins, particularly those recently reported as key contributors to long COVID symptoms and neurodegeneration^3,8,38. Using the NS-PASC group as a reference, six DEPs (TREM2, C1QA, SPON-1, CXCL10, IL-4, and VCAM-1) showed significant differences in the Cog-PASC group, while four DEPs (C2, CD33, PDGF-β, and TNF) differed significantly in the Other-PASC group (Fig. 3h). Among these, TREM2, CXCL10, IL-4, VCAM-1, CD33, and TNF are inflammatory proteins^4,8,38. C2 and C1QA are part of the complement system³, and PDGF-β regulates pericytes⁸, maintaining vascular function⁴, including the BBB³⁹. SPON-1 is involved in neuronal regulation and cell adhesion⁴. All these proteins, except IL-4 and PDGF-β, were upregulated in the Cog-PASC group. The downregulation of IL-4 and PDGF-β may reflect impaired anti-inflammatory and vascular homeostatic processes (Fig. 3h). Functionally, these proteins were also associated with cognitive function. Regression analysis showed that MoCA scores were positively associated with IL-4 levels (Fig. 3i), while higher FAS scores correlated with increased CD33 and decreased PDGF-β, and elevated TNF levels were associated with higher PASC scores.

A multivariable logistic model using the least absolute shrinkage and selection operator (LASSO)⁴⁰ method on 54 DEPs (44 Cog-PASC-related and 10 immune/vascular regulatory proteins) identified CASQ2, ARHGAP1, and TREM2 as key predictors (Fig. 3j, k), achieving an area under the curve of 0.889 in the receiver operating characteristic analysis. These findings suggest that these proteins alone effectively identify individuals at risk for Cog-PASC, underscoring their potential pathogenic relevance.

Taken together, the Cog-PASC group exhibited distinct DEPs related to oxidative stress and synaptic dysfunction, along with alterations in immune and vascular regulatory proteins. Many of these proteins were significantly associated with cognitive performance, and several (CASQ2, ARHGAP1, and TREM2) emerged as independent predictors of Cog-PASC in multivariable modeling. These findings suggest that pathways involving synaptic regulation, oxidative stress responses, and immune and vascular interactions may contribute to the pathogenesis of Cog-PASC and could help identify individuals at risk.

Brain alterations in Cog-PASC replicated in an independent cohort

We used the validation cohort (Fig. 1) as an independent dataset to replicate the important findings from the exploration cohort. A total of 109 patients were included: 16 with Cog-PASC, 47 with Other-PASC, and 46 with NS-PASC (Table 5). The cohort comprised 72 females (66.1%). Participants were enrolled a median of 16.0 months after infection [IQR 10.0–22.0], and MRI was performed at a median of 18.0 months [IQR 11.0–23.0] post-infection, both significantly longer than in the exploration cohort (p < 0.001 for both). As in the exploration cohort, most participants were infected during the Omicron-dominant period.

Table 5 Baseline characteristics of the participants in the validation cohort

The Cog-PASC group tended to be older, less educated, and less frequently female; these variables were adjusted for in subsequent analyses. This group showed more severe cognitive impairment, whereas the Other-PASC group had higher fatigue scores. Overall, PASC scores and symptom prevalence were comparable between the Cog-PASC and Other-PASC groups (Table 5 and Supplementary Fig. 6a, b).

Blood biomarker analysis using Simoa technology replicated the finding of elevated brain damage-associated proteins in the Cog-PASC group; both GFAP and NfL levels were significantly higher than in the other groups, suggesting more pronounced neuronal and glial damage (Fig. 4a, b). MRI analysis confirmed widespread cortical thinning in the Cog-PASC group, most notably in the frontal, cingulate, insular, and parietal cortices (Table 6 and Fig. 4c). Cingulate cortical thickness was positively associated with MoCA scores, independent of demographic covariates (Fig. 4d). Volumetric analyses revealed significant volume reductions in the whole cortex and parietal cortex.

Fig. 4: Validation cohort analysis: brain injury biomarkers, structural MRI features, and perivascular diffusion metrics.

a, b Levels of glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) in the validation cohort across NS-PASC (n = 44), Other-PASC (n = 45), and Cog-PASC (n = 16). c, d Cortical thickness (mm) across brain regions (c) and standardized beta coefficients (β) from regression models relating MoCA scores to thickness in the frontal, cingulate, insular, and parietal cortices NS-PASC (n = 44), Other-PASC (n = 45), and Cog-PASC (n = 16). d Effect sizes are presented as heat maps. Paramagnetic susceptibility (ppm) across cortical regions (e) and standardized β coefficients from regression models linking MoCA scores to iron deposition in the occipital cortex, caudate, putamen, and hippocampus ((NS-PASC (n = 25), Other-PASC (n = 39), and Cog-PASC (n = 14)) (f). Choroid plexus volume (CPV) fraction and DTI-ALPS index by group. DTI-ALPAS (NS-PASC (n = 46), Other-PASC (n = 46), and Cog-PASC (n = 16) (g), and standardized β coefficients from regression models relating these metrics to MoCA scores (h). Significant differences were observed between Cog-PASC and both NS-PASC and Other-PASC in (g) (***p < 0.001). For all box plots, the center line indicates the median, box boundaries the interquartile range (IQR; 25th–75th percentiles), and whiskers extend to the most extreme data points within 1.5 × IQR. Data points beyond whiskers are shown as outliers. Group comparisons were conducted using Two-sided ANCOVA, adjusting for age, sex, and education. Regression models were adjusted for the same covariates. All p-values were corrected for multiple comparisons using the false discovery rate (FDR); significance levels are indicated as *adjusted p < 0.05, **adjusted p < 0.01, and ***adjusted p < 0.001. Exact p-values are provided in the Source Data file.

Table 6 Parameters of magnetic resonance imaging: thickness and paramagnetic susceptibility in the validation cohort

The Cog-PASC group also showed increased paramagnetic susceptibility in the occipital cortex, caudate, putamen, and hippocampus, consistent with the exploration cohort (Fig. 4e), although susceptibility values were not associated with MoCA scores (Fig. 4f). Additional structural measures showed a significantly larger choroid plexus volume and a reduced DTI-ALPS index in the Cog-PASC group (Fig.4g), although no significant associations were observed between choroid plexus volume or DTI-ALPS index and MoCA scores (Fig. 4h). In DTI-based TBSS analysis, the Cog-PASC group demonstrated elevated MD and RD alongside reduced FA across bilateral white matter regions compared with the NS-PASC and Other-PASC groups (P_FWE < 0.05), a pattern suggestive of microstructural white matter injury and potential demyelination²⁰ (Table 6).

Taken together, the validation cohort reproduced key findings from the exploration cohort, confirming that individuals with a history of mild COVID-19 who present with cognitive symptoms exhibit structural brain changes suggestive of neurodegeneration, including cortical thinning, volume loss, iron accumulation, CP enlargement, and microstructural white matter injury.

This study identified distinct structural and neurodegenerative changes in the brains of individuals with Cog-PASC that were not evident in other-PASC groups, most of whom had not been hospitalized during the acute phase, that were not observed in other-PASC groups. These results were independently replicated in a separate validation cohort, suggesting that Cog-PASC may involve unique neuropathological processes and highlighting the need for targeted monitoring strategies in affected individuals.

Although brain injury has been reported in moderate-to-severe cases of acute COVID-19⁴¹, whether this damage persists and leads to chronic neurodegeneration is unclear. Recent biomarker studies, primarily focused on post-hospitalized individuals, have suggested increased brain injury in the chronic phase^10,42. However, other studies, particularly those involving non-hospitalized individuals, did not confirm persistent brain damage^43,44, indicating limited ongoing injury. In this study, which included a larger cohort of predominantly non-hospitalized individuals^43,44, we found evidence of chronic brain injury and neurodegenerative changes in the Cog-PASC group across both the exploration and validation cohorts. Specifically, elevated GFAP and/or NfL levels were observed without corresponding alterations in β-amyloid or phosphorylated tau proteins. This is notable, as SARS-CoV-2 infection has been linked to AD pathogenesis, with viral proteins potentially forming structures that may drive amyloid formation, and in vitro data showing increased tau phosphorylation and aggregation due to SARS-CoV-2⁴⁵. The brain injury observed in this population, approximately one year post-infection, may represent a distinct process from classical AD, where mild cognitive impairment typically involves β-amyloid and tau abnormalities⁴⁶. These results warrant further neuropathologic investigation.

Cortical thickness was significantly reduced in the cingulate cortex, parahippocampal gyrus, and insular cortex of the Cog-PASC group compared with the Other-PASC group in the exploration cohort, with only modest differences relative to the NS-PASC group. In the covariate-matched cohort, cingulate cortical thickness remained significantly lower in the Cog-PASC. These findings were confirmed in the validation cohort, where the Cog-PASC group showed the greatest cortical thinning in the cingulate and insular cortices, as well as in the frontal and parietal cortices. The affected regions are consistent with those reported in previous post-COVID brain studies^5,7,8. Meanwhile, brain volume analyses in the exploration cohort revealed no significant differences among PASC groups, whereas in the validation cohort, the Cog-PASC group showed volume reductions in the whole cortex and parietal cortex. These discrepant results suggest that brain volume may be less sensitive to detecting post-COVID structural changes. This aligns with previous reports indicating that cortical thickness is less influenced by intracranial volume and race and is more sensitive to pathological aging than volumetric measures^47,48,49, thereby providing a more reliable marker of subtle neuroanatomical change. The greater disparity in cortical thickness between the Cog-PASC and Other-PASC groups, compared with the Cog-PASC and NS-PASC groups, warrants further discussion. Cortical thinning in the Cog-PASC group could reflect a reduced brain functional reserve⁵, which indicates vulnerability to cognitive impairment⁸, rather than being a result of significant brain damage. Another possibility is cortical enlargement in the Other-PASC group, possibly due to neurogenesis or compensatory mechanisms, as reported particularly in mild COVID cases^50,51. Neurogenesis, potentially supported by enhanced CP function, may increase gray matter⁵², while compensatory mechanisms could cause cortical hypertrophy⁵³. Despite modest cortical thinning, the Cog-PASC group showed elevated brain damage-associated proteins, decreased oxidative stress-related proteins, and increased inflammatory markers, which are molecular signatures associated with gray matter loss and potential long-term structural vulnerability.

Using the χ-separation method to isolate paramagnetic iron susceptibility, we observed increased cortical iron deposition in the Cog-PASC group within the exploration cohort, most notably in the cingulate, occipital cortex, and hippocampus, compared with the NS-PASC and Other-PASC groups. In the covariate-matched cohort, iron accumulation was most prominent in the cingulate. Analysis of the validation cohort further confirmed elevated iron levels, particularly in the occipital cortex, hippocampus, caudate, and putamen. Iron accumulation may contribute to neurodegeneration through two key mechanisms^11,54: (1) generating reactive oxygen species that induce oxidative damage and ferroptosis^11,54,55 and (2) promoting the aggregation of neurodegenerative proteins⁵⁴. Excess iron may also aggravate BBB disruption by inducing oxidative stress and neuroinflammation, leading to microglial activation and the release of cytokines and matrix metalloproteinases that degrade tight junctions and basement membranes⁵⁶. Chronic iron overload further promotes endothelial ferroptosis and vascular remodeling⁵⁶, potentially amplifying vascular injury initiated by SARS-CoV-2 binding to ACE2 receptors on brain microvascular endothelial cells⁵⁷.

Notably, the covariate-matched cohort, which minimizes confounding by age, sex, and education, revealed a convergence of structural and metabolic alterations in the cingulate cortex of Cog-PASC individuals, including both significant cortical thinning and iron deposition. This dual burden suggests that the cingulate may serve as a key substrate for persistent cognitive impairment in long COVID. The cingulate cortex is essential for attentional control, emotional regulation, and cognitive integration, and is particularly sensitive to neuroinflammatory and oxidative stress–mediated injury^58,59. Iron accumulation may further exacerbate regional vulnerability by promoting microglial activation and synaptic dysfunction, while cortical thinning may reflect neuronal or glial loss. These findings are consistent with prior reports of anterior cingulate thinning in post-COVID patients⁵ and with broader literature implicating the cingulate in cognitive impairment across neuropsychiatric conditions⁶⁰.

The CP was larger in the Cog-PASC group compared to the Other-PASC group, suggesting that structural alterations in the CP may contribute to the cognitive manifestations of PASC. As a multifunctional structure, the CP forms the blood–CSF barrier, produces CSF, supplies nutrients, and supports waste clearance and immune surveillance¹⁴. Structural changes in the CP, such as epithelial flattening and vessel wall thickening, have been observed in aging as well as in patients with AD⁶¹. MRI studies have also reported increased CP volume in individuals with mild cognitive impairment, AD, and PD^15,16, suggesting that CP enlargement may serve as a biomarker of CP dysfunction⁶².

DTI-ALPS and other diffusivity measures (MD, RD, and FA) showed no statistically significant differences in the exploration cohort, although the direction of change in the Cog-PASC group (higher MD and RD, lower FA) was consistent with our hypothesis. In the validation cohort, however, the DTI-ALPS index was significantly reduced, while MD and RD were increased and FA decreased, indicating more pronounced microstructural alterations. A lower DTI-ALPS index suggests impaired glymphatic function and reduced interstitial fluid clearance, whereas increased MD and RD, together with decreased FA, are compatible with white matter injury involving demyelination or axonal degeneration. Similar reductions have been observed in COVID-19 patients three months post-infection⁶³. These findings support the view that long COVID may involve both functional glymphatic disruption and structural compromise of white matter integrity, warranting further investigation in larger long COVID cohorts.

Blood proteomic analyses revealed significant alterations in proteins involved in oxidative stress and synaptic function, which are both associated with neurodegeneration. A multivariable model identified TREM2, ARHGAP1, and CASQ2 as key DEPs independently associated with cognitive impairment. TREM2, a microglial receptor responsible for clearing pathological proteins and promoting neuroprotection⁶⁴, is markedly upregulated in severe COVID-19, particularly in T cells and mononuclear cells, where it enhances immune activation and proinflammatory signaling via interactions with the SARS-CoV-2 membrane protein⁶⁵. This upregulation may contribute to persistent neuroinflammation and immune dysregulation, potentially accelerating neurodegenerative processes⁶⁵. ARHGAP1 regulates Rho GTPase activity, influencing cytoskeletal remodeling and cell polarity⁶⁶. Although its direct role in neurodegeneration is unclear, dysregulation of Rho/ROCK signaling may affect microglial function and synaptic pruning⁶⁷. CASQ2 is a calcium-binding protein that regulates calcium storage, primarily in cardiac muscle⁶⁸, and is the predominant isoform in the hippocampus, where it supports neuronal calcium balance and synaptic plasticity⁶⁸. Disruption of CASQ2 may impair calcium homeostasis and contribute to neuroinflammation and neurodegeneration.

The convergence of structural MRI findings and proteomic alterations in the Cog-PASC group provides insight into potential pathophysiologic mechanisms. Cortical thinning, particularly in the cingulate and insular cortices, may be linked to the observed downregulation of synaptic regulatory proteins, reflecting impaired synaptic maintenance and neuronal connectivity. Similarly, increased cortical and subcortical iron deposition could exacerbate oxidative stress, consistent with the reduced abundance of antioxidant enzymes such as SOD1 and CCS detected in the proteomic analysis. CP enlargement, observed on MRI, may also contribute to impaired waste clearance and chronic neuroinflammation, potentially sustaining the upregulation of inflammatory proteins including TREM2, CXCL10, and VCAM-1. Together, these findings suggest that structural brain alterations and molecular signatures are part of a converging cascade involving synaptic dysfunction, oxidative stress, and immune dysregulation, which may underlie the persistent cognitive deficits observed in Cog-PASC.

Long-COVID symptoms, aside from cognitive dysfunction, did not significantly differ between Other-PASC and Cog-PASC groups. Notably, FAS and PASC scores, unlike cognitive symptom scores, showed no association with blood markers of brain injury or structural changes, but instead correlated with several immune and vascular regulatory proteins. Specifically, higher FAS scores were linked to increased CD33 and decreased PDGF-β, while higher PASC scores were associated with elevated TNF levels. Elevated CD33 expression in severe COVID-19 has been associated with immunosuppressive myeloid responses, which may indirectly suppress T-cell activity⁶⁹, impair antiviral defense, and contribute to chronic inflammation and fatigue. Reduced PDGF-β levels can impair vascular repair by disrupting pericyte recruitment and endothelial stability, thereby worsening hypoxia and tissue stress⁷⁰. Elevated TNF levels in PASC may drive persistent inflammation through sustained activation of TNF-producing T cells and macrophages, leading to tissue damage and fatigue^71,72. TNF also synergizes with IL-1β and IL-6 to amplify NF-κB signaling and exacerbate endothelial dysfunction^71,72. It is worth noting that our previous study demonstrated that patients with the PASC symptom cluster, including fatigue and post-exertional malaise, had different blood cytokine profiles compared to those with the PASC symptom cluster, including cognitive dysfunction (KJIM in major revision). The course of long-COVID symptoms, particularly cognitive impairment, may be influenced by patient-specific factors such as brain functional reserve and CP volume, leading to differentiation into Cog-PASC and Other-PASC groups. Hence, our findings suggest that cognitive symptoms may have different pathophysiologic mechanisms from other-PASC symptoms. Further studies are needed for these distinct Cog-PASC patients to elucidate biomarkers for diagnosis and potential therapeutic targets.

Our study has several limitations. First, it employed a cross-sectional design, which identifies associations but not cause-and-effect relationships. As this is a preliminary report from a longitudinal study with follow-up MRI findings, future reports will provide more details on the clinical courses and long-term consequences of MRI findings and blood proteomic signatures. Second, this study lacks stratification by case severity, as the majority (~98%) of participants were non-hospitalized patients with only mild acute symptoms. Therefore, our results may not apply to patients who experienced more severe COVID-19 symptoms. Third, baseline characteristics such as age, sex, and education were not evenly distributed across groups. Although adjustments were made for these variables, results should be interpreted with caution. Fourth, the exploration and validation cohorts were not fully comparable, with differences such as enrollment and MRI timing. This may limit comparability, and the relatively small sample size further increases susceptibility to random variation, potentially contributing to discrepancies between cohorts, particularly in volumetric and DTI analyses. Nonetheless, the consistent direction of changes across cohorts supports the biological relevance of the findings. Finally, this study was conducted at a single tertiary medical center in Korea within a single ethnic group, limiting the generalizability of the findings.

In conclusion, our study suggests distinct brain structural alterations and ongoing neurodegenerative processes in individuals with cognitive dysfunction, which are not prominent in those with other symptoms among PASC. Hence, the pathogenesis underlying cognitive dysfunction in long COVID differs from non-cognitive symptoms, while its long-term course and clinical significance should be confirmed in future longitudinal studies.

This is a preliminary report from the exploration cohort of the LOCOMOTIVE study (LOng Covid Outcome MOnitoring with Translational InVEstigations of blood and neuroimaging), an ongoing prospective, longitudinal cohort study investigating neurological symptoms and brain structural changes associated with long COVID. The study evaluates longitudinal changes in symptoms, brain MRI findings, and blood profiles. Brain MRI scans are conducted at baseline and 1 year to assess structural changes, including gray matter alterations. Blood samples are collected at baseline, 6 months, and 1 year, with symptom evaluations every 3 months.

Registered with the Clinical Research Information Service (cris.nih.go.kr, KCT0007848), participants for the exploration cohort were recruited between November 2022 and October 2023 from a tertiary medical center (Asan Medical Center, Seoul, South Korea), followed by validation cohort recruitment from November 2023 to April 2025. This preliminary analysis focused on potential brain damage, structural alterations, and neurodegenerative processes following SARS-CoV-2 infection.

Healthy individuals with no prior cognitive complaints or impairments in daily living activities before contracting SARS-CoV-2 were eligible for enrollment; however, their data were not included in this study. Exclusion criteria included cognitive complaints before COVID-19, acute illnesses within the past two months (e.g., myocardial infarction, unstable angina, pneumonia), active cancer⁷³, autoimmune diseases requiring immunosuppressants, neurodegenerative conditions (e.g., Alzheimer’s disease, Parkinson’s disease), and psychiatric disorders.

Participants underwent blood sampling and assessments using standardized tools, including the Montreal Cognitive Assessment (MoCA) for cognitive function⁷⁴, the Fatigue Assessment Scale (FAS) for fatigue⁷⁵, and detailed questionnaires to evaluate post-acute sequelae of COVID-19 (PASC) symptoms^76,77. The PASC symptoms assessed included post-exertional malaise, fatigue, brain fog, dizziness, gastrointestinal symptoms, palpitations, changes in sexual desire or capacity, loss or change in smell or taste, thirst, chronic cough, chest pain, and abnormal movements¹. Symptom severity during the acute phase of COVID-19 was determined using the World Health Organization (WHO) ordinal scale⁷⁸.

Sex was recorded as assigned at birth (ascertained from medical records at enrollment). Although sex was not a primary variable of interest in the study design, baseline differences between groups were observed. Therefore, sex was included as a covariate in statistical analyses to adjust for potential confounding effects.

All participants provided written informed consent in accordance with the Declaration of Helsinki. The study protocol was approved by the Institutional Review Board of Asan Medical Center (IRB No. 2022–1378). Transportation and examination costs for study visits were reimbursed, but no additional financial or other benefits were provided.

Classification of the participants

Participants with SARS-CoV-2 infection were categorized into three groups based on cognitive impairment and other post-acute sequelae of COVID-19 (PASC). The Cog-PASC group included individuals with cognitive impairment (MoCA score <26)⁷⁴. The Other-PASC group comprised those without cognitive impairment but with significant fatigue (FAS score ≥22)⁷⁵ and/or other-PASC symptoms (PASC score ≥12)^76,77. Patients who did not meet the criteria for either of these groups were classified into the no significant PASC (NS-PASC) group.

Matching cohort

Due to significant differences in age, sex, and education level among the PASC groups, we constructed a covariate-matched cohort to minimize potential demographic confounding. Participants were matched in a 1:1 ratio using nearest-neighbor matching without replacement, based on propensity scores estimated from a logistic regression model that included age, sex, and education level as covariates. A caliper width of 1.5 standard deviations of the logit of the propensity score was applied for the Non-PASC versus Cog-PASC comparison, and 2.0 standard deviations for the Other-PASC versus Cog-PASC comparison. Matching balance was evaluated using standardized mean differences (SMDs) for each covariate, with an SMD below 0.1 considered indicative of adequate balance. After matching, group differences were assessed using independent t-tests for continuous variables (age, education level) and Fisher’s exact test for the categorical variable (sex).

Blood sampling and protein analysis

Blood samples were collected and stored at −80 °C following standardized procedures⁷⁹, then analyzed using advanced platforms. Brain damage markers, including GFAP, NFL, p-Tau181, and the Aβ40/42 ratio, were measured using the Simoa HD-X platform. Assay results were reported in pg/mL, with data normalized according to the manufacturer’s protocol. Proteomic analysis utilized the Olink Explore 3,072 platform, which measures proteins linked to inflammation, neurology, oncology, and cardiometabolic pathways using Proximity Extension Assay (PEA) technology. Protein concentrations were transformed into NPX values on a log₂ scale, where a 1 NPX increase equates to a protein concentration doubling.

Differentially expressed protein analysis

Multivariate linear regression, adjusted for age and sex, identified differentially expressed proteins (DEPs) with adjusted p-values < 0.05 using the Benjamini–Hochberg method to control the false discovery rate (FDR). DEPs were visualized using volcano plots, with additional box and principal component analysis (PCA) plots generated in R (ggplot2, version 4.4.1).

Gene set enrichment and pathway analysis

Enrichment analysis of DEPs used the Human Protein Atlas (HPA) dataset³³ and Gene Ontology (GO) terms, including biological processes, molecular functions, and cellular components³⁴. Bubble plots visualized functional associations in R. Pathway analysis integrated data with the Kyoto Encyclopedia of Genes and Genomes (KEGG) to map interactions and pathways³⁵. Protein–protein interaction (PPI) networks provided an intuitive view of GO terms’ significance and prevalence.

Protein–protein interaction network analysis

A PPI network was created using the STRING database (minimum interaction score: 0.4)³⁶, with nodes representing proteins and edges indicating functional associations. Stronger interactions were shown with thicker edges. Key clusters were identified through K-means clustering, with centrality assessed by node degree—higher degrees indicated greater connectivity and biological significance.

MRI acquisition

MRI data were collected using 3.0-Tesla scanners (Ingenia CX, Philips Healthcare) with a 32-channel head coil, following protocols tailored for neurodegenerative diseases. Sequences included 3D T1-WI for cortical parcellation, DTI for ALPS index calculation, and multiecho gradient echo (GRE) for paramagnetic susceptibility maps. Detailed acquisition parameters are in Supplementary Table 2.

Cortical parcellation using FreeSurfer

Cortical thickness and its volumes were measured on 3D T1-WI using FreeSurfer (v.7.3)^80,81. Processing steps included removing non-brain tissue, Talairach transformation, intensity normalization, and segmentation of gray (GM) and white matter (WM). The cortical surface was parcellated into regions of interest (ROIs) using the Desikan-Killiany Atlas⁸², then grouped into lobar regions such as the frontal, parietal, temporal, occipital, insular, and cingulate cortices⁸³. Additionally, following a previous report on greater reductions of cortical thickness in the orbitofrontal cortex, cingulate cortex, and parahippocampal gyrus among patients with COVID infection⁵, we included these regions a priori.

Paramagnetic susceptibility maps

Multiecho GRE images were post-processed to generate paramagnetic susceptibility maps⁸⁴. Phase maps were unwrapped using a Laplacian algorithm⁸⁵, and background field removal isolated tissue-specific fields. R2* maps were derived by fitting a mono-exponential model to the GRE signal magnitude. These were applied to susceptibility source separation using the χ-separation toolbox, producing paramagnetic susceptibility maps³². Cortical and deep GM regions were segmented using SynthSeg⁸⁴, a tool optimized for diverse image contrasts and resolutions. Segmentation masks were directly overlaid onto the susceptibility maps to obtain susceptibility values without requiring co-registration.

Choroid plexus segmentation

Choroid plexus volumes (CPVs) were segmented from FreeSurfer-derived 3D T1-WI masks of the lateral and inferior lateral ventricles. Using a Gaussian mixture model (GMM), voxels were grouped by intensity, distinguishing cerebrospinal fluid (CSF) from choroid plexus voxels⁸⁶. The GMM method outperforms FreeSurfer’s segmentation^87,88. All automated masks were reviewed and corrected by an experienced neuroradiologist. CPV was normalized by dividing by total intracranial volume (TIV), yielding the CPV fraction.

DTI-ALPS processing

DTI-ALPS preprocessing followed established methods^87,88,89, with ALPS indices calculated using a MATLAB-based in-house program (DTI-ALPS Analyzer, MATLAB 9.6, version 2019b, the Mathworks, Inc). The detailed calculation steps are provided in Supplementary Methods. Diffusion coefficient maps (Dx, Dy, Dz) were generated, and fractional anisotropy (FA) maps were used to define ROIs on projection, association, and subcortical white matter fibers. Subject-specific 5-mm spherical ROIs were manually drawn on the slice containing the uppermost portion of the left lateral ventricle using color-coded FA maps, where three ROIs were defined according to their directions along the projection, association, and subcortical fibers (Supplementary Fig. 7). A blinded radiologist with 11 years of experience performed the delineation. After a ~30-week washout period, the ROIs were redrawn to assess intraobserver reliability, yielding an intraclass correlation coefficient (ICC) of 0.603 (95% confidence interval, 0.49–0.69; P < 0.001), comparable with previous reports⁹⁰.

The ALPS index, calculated as the mean diffusion in projection and association fibers divided by the mean in orthogonal fibers [mean(Dxassoc, Dxproj)/mean(Dzassoc/Dyproj)], reflects the water molecules’ diffusivity along the radial direction at the lateral ventricular body level. A lower ALPS index suggests impaired water diffusion along perivascular spaces and potential dysfunction in waste clearance⁸⁹. Furthermore, voxel-wise comparisons of mean diffusivity (MD), radial diffusivity (RD), and FA among the three groups were performed using Tract-Based Spatial Statistics (TBSS), a widely used method for spatial statistical analysis based on the white matter skeleton⁹¹. TBSS enables precise detection of microstructural alterations in white matter and has become a widely adopted approach for investigating white matter fiber tracts^20,92,93. The analysis included age, sex, and education as covariates for adjustment. Multiple comparison correction was performed using the family-wise error (FWE) method, with statistical maps thresholded at p < 0.05 (two-sided).

Statistical analysis

All statistical analyses were performed using R version 4.1.1. (R Foundation for Statistical Computing, Vienna, Austria). Analyses were conducted separately in the exploration cohort, the covariate-matched cohort constructed based on age, sex, and education level, and the independent validation cohort. Descriptive statistics were used to summarize demographic and clinical variables, including medians and interquartile ranges (IQRs) for continuous variables and frequencies and percentages for categorical variables. Group comparisons were conducted using the Kruskal–Wallis test with Dunn’s correction for multiple comparisons. Additionally, analysis of covariance (Two-sided ANCOVA) was performed to compare biomarker levels across the three groups, adjusting for age, sex, and education as covariates. Group differences were assessed by comparing adjusted means within the model, with Tukey’s Honest Significant Difference (HSD) test used for post hoc multiple comparisons. For MRI parameter comparisons across the three groups, false discovery rate (FDR) correction was applied to control for multiple comparisons. Intraclass correlation coefficients (ICC) were calculated using a two-way consistency model.

To identify differentially expressed proteins (DEPs) relevant to Cog-PASC, volcano plot analysis was conducted based on multivariate linear regression, with p-values corrected for multiple comparisons using the Benjamini–Hochberg method to control the FDR. Pearson correlation matrices were constructed to assess the linear relationships between biomarkers, clinical variables, and MRI parameters. The multivariable logistic regression model for cognitive impairment prediction was constructed using the least absolute shrinkage and selection operator (LASSO) method to optimize variable selection and prevent overfitting. Model performance was evaluated using multiple metrics. The discriminative ability of the model was assessed using the area under the Receiver Operating Characteristic curve (AUC-ROC), while diagnostic accuracy was measured through sensitivity and specificity calculations. The overall accuracy of the model and its corresponding confidence intervals were calculated to determine model stability. Additional model validation was conducted using McFadden’s R² and Kappa statistics, while model calibration was assessed using McNemar’s test.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

De-identified, processed protein-level intensity tables, together with aggregated clinical variables, are available in this study through the Clinical & Omics Data Archive (CODA) of the National Institute of Health of South Korea (https://coda.nih.go.kr/frt/index.do; email: <a href="mailto:coda@korea.kr">coda@korea.kr</a>). The CODA Committee reviews academic applications accompanied by required documents (e.g., research protocol, IRB approval, human resources utilization plan) to determine eligibility for data access and sharing. Approved researchers are granted secure access for a defined period under conditions ensuring compliance with ethical and legal requirements. Additional datasets generated as part of this ongoing investigator-initiated cohort may be made available to qualified researchers for non-commercial academic purposes upon reasonable request. Such requests should be directed to the corresponding authors ([eunjae.lee@amc.seoul.kr; kimsunghanmd@hotmail.com]). Source data are provided with this paper.

No custom software was developed during this study. Open-source packages and libraries and corresponding versions used during the computational analysis are described in the “Methods” section and the Reporting summary.

Nalbandian, A. et al. Post-acute COVID-19 syndrome. Nat. Med. 27, 601–615 (2021).
Article CAS PubMed PubMed Central Google Scholar
Davis, H. E., McCorkell, L., Vogel, J. M. & Topol, E. J. Long COVID: major findings, mechanisms and recommendations. Nat. Rev. Microbiol 21, 133–146 (2023).
Article CAS PubMed PubMed Central Google Scholar
Cervia-Hasler, C. et al. Persistent complement dysregulation with signs of thromboinflammation in active Long Covid. Science 383, eadg7942 (2024).
Article CAS PubMed Google Scholar
Liew, F. et al. Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease. Nat. Immunol. 25, 607–621 (2024).
Article CAS PubMed PubMed Central Google Scholar
Douaud, G. et al. SARS-CoV-2 is associated with changes in brain structure in UK Biobank. Nature 604, 697–707 (2022).
Article ADS CAS PubMed PubMed Central Google Scholar
Díez-Cirarda, M. et al. Multimodal neuroimaging in post-COVID syndrome and correlation with cognition. Brain 146, 2142–2152 (2023).
Article PubMed Google Scholar
Hosp, J. A. et al. Cerebral microstructural alterations in Post-COVID-condition are related to cognitive impairment, olfactory dysfunction and fatigue. Nat. Commun. 15, 4256 (2024).
Article ADS CAS PubMed PubMed Central Google Scholar
Greene, C. et al. Blood-brain barrier disruption and sustained systemic inflammation in individuals with long COVID-associated cognitive impairment. Nat. Neurosci. 27, 421–432 (2024).
Article CAS PubMed PubMed Central Google Scholar
Lee, M.-H. et al. Microvascular injury in the brains of patients with Covid-19. N. Engl. J. Med 384, 481–483 (2021).
Article PubMed Google Scholar
Wood, G. K. et al. Post-hospitalisation COVID-19 cognitive deficits at one year are global and associated with elevated brain injury markers and grey matter volume reduction. Nat. Med. 31, 245–257 (2025).
Article CAS PubMed Google Scholar
Ward, R. J., Zucca, F. A., Duyn, J. H., Crichton, R. R. & Zecca, L. The role of iron in brain ageing and neurodegenerative disorders. Lancet Neurol. 13, 1045–1060 (2014).
Article CAS PubMed PubMed Central Google Scholar
Schenck, J. F. The role of magnetic susceptibility in magnetic resonance imaging: MRI magnetic compatibility of the first and second kinds. Med. Phys. 23, 815–850 (1996).
Article CAS PubMed Google Scholar
Ayton, S., Faux, N. G., Bush, A. I. & Alzheimer’s Disease Neuroimaging, I. Ferritin levels in the cerebrospinal fluid predict Alzheimer’s disease outcomes and are regulated by APOE. Nat. Commun. 6, 6760 (2015).
Article CAS PubMed Google Scholar
Solar, P., Zamani, A., Kubickova, L., Dubovy, P. & Joukal, M. Choroid plexus and the blood-cerebrospinal fluid barrier in disease. Fluids Barriers CNS 17, 35 (2020).
Article PubMed PubMed Central Google Scholar
Choi, J. D. et al. Choroid plexus volume and permeability at brain MRI within the Alzheimer disease clinical spectrum. Radiology 304, 635–645 (2022).
Article PubMed Google Scholar
Jeong, S. H. et al. Association of choroid plexus volume with motor symptoms and dopaminergic degeneration in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 94, 1047–1055 (2023).
Article PubMed Google Scholar
Eide, P. K. et al. Plasma neurodegeneration biomarker concentrations associate with glymphatic and meningeal lymphatic measures in neurological disorders. Nat. Commun. 14, 2084 (2023).
Article ADS CAS PubMed PubMed Central Google Scholar
Rasmussen, M. K., Mestre, H. & Nedergaard, M. The glymphatic pathway in neurological disorders. Lancet Neurol. 17, 1016–1024 (2018).
Article CAS PubMed PubMed Central Google Scholar
Taoka, T. et al. Diffusion tensor image analysis along the perivascular space (DTI-ALPS): revisiting the meaning and significance of the method. Magn. Reson. Med. Sci. 23, 268–290 (2024).
Article CAS PubMed PubMed Central Google Scholar
Tae, W.-S., Ham, B.-J., Pyun, S.-B., Kang, S.-H. & Kim, B.-J. Current clinical applications of diffusion-tensor imaging in neurological disorders. J. Clin. Neurol. 14, 129 (2018).
Article PubMed PubMed Central Google Scholar
Verheggen, I., Van Boxtel, M., Verhey, F., Jansen, J. & Backes, W. Interaction between blood-brain barrier and glymphatic system in solute clearance. Neurosci. Biobehav. Rev. 90, 26–33 (2018).
Article CAS PubMed Google Scholar
Lee, E. J. et al. Clinical implication of serum biomarkers and patient age in inflammatory demyelinating diseases. Ann. Clin. Transl. Neurol. 7, 992–1001 (2020).
Article CAS PubMed PubMed Central Google Scholar
Barro, C. et al. Serum GFAP and NfL levels differentiate subsequent progression and disease activity in patients with progressive multiple sclerosis. Neurol. Neuroimmunol. Neuroinflamm. 10, e200052 (2023).
Article PubMed Google Scholar
Beltran, T. A. Normative values for serum neurofilament light chain in US adults. J. Clin. Neurol. 20, 46 (2024).
Article PubMed PubMed Central Google Scholar
Palmqvist, S. et al. Discriminative accuracy of plasma phospho-tau217 for Alzheimer disease vs other neurodegenerative disorders. JAMA 324, 772–781 (2020).
Article CAS PubMed Google Scholar
Gonzalez-Ortiz, F. et al. Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer’s disease. Nat. Commun. 15, 2908 (2024).
Article ADS CAS PubMed PubMed Central Google Scholar
Woodruff, M. C. et al. Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID. Nat. Commun. 14, 4201 (2023).
Article ADS CAS PubMed PubMed Central Google Scholar
Stephenson, E. et al. Single-cell multi-omics analysis of the immune response in COVID-19. Nat. Med. 27, 904–916 (2021).
Article CAS PubMed PubMed Central Google Scholar
Duijvelaar, E., Gisby, J., Peters, J. E., Bogaard, H. J. & Aman, J. Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients. Nat. Commun. 15, 744 (2024).
Article ADS CAS PubMed PubMed Central Google Scholar
Filbin, M. R. et al. Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions. Cell Rep. Med. 2, 100287 (2021).
Article PubMed PubMed Central Google Scholar
Bland, A. et al. Profiles of objective and subjective cognitive function in Post-COVID Syndrome, COVID-19 recovered, and COVID-19 naïve individuals. Sci. Rep. 14, 13368 (2024).
Article ADS CAS PubMed PubMed Central Google Scholar
Min, K. et al. A human brain atlas of χ-separation for normative iron and myelin distributions. NMR Biomed. 37, e5226 (2024).
Article CAS PubMed Google Scholar
Uhlén, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).
Article PubMed Google Scholar
Consortium, G. O. The gene ontology resource: 20 years and still GOing strong. Nucleic Acids Res. 47, D330–D338 (2019).
Article Google Scholar
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).
Article CAS PubMed Google Scholar
Szklarczyk, D. et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607–D613 (2019).
Article CAS PubMed Google Scholar
Karlsson, M. et al. A single–cell type transcriptomics map of human tissues. Sci. Adv. 7, eabh2169 (2021).
Article ADS CAS PubMed PubMed Central Google Scholar
Hou, J., Chen, Y., Grajales-Reyes, G. & Colonna, M. TREM2 dependent and independent functions of microglia in Alzheimer’s disease. Mol. Neurodegener. 17, 84 (2022).
Article CAS PubMed PubMed Central Google Scholar
Smyth, L. C. et al. Characterisation of PDGF-BB: PDGFRβ signalling pathways in human brain pericytes: evidence of disruption in Alzheimer’s disease. Commun. Biol. 5, 235 (2022).
Article CAS PubMed PubMed Central Google Scholar
Tibshirani, R. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Ser. B Methodol. 58, 267–288 (1996).
Article MathSciNet Google Scholar
Kanberg, N. et al. Neurochemical evidence of astrocytic and neuronal injury commonly found in COVID-19. Neurology 95, e1754–e1759 (2020).
Article CAS PubMed Google Scholar
Michael, B. D. et al. Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses. Nat. Commun. 14, 8487 (2023).
Article ADS CAS PubMed PubMed Central Google Scholar
Kanberg, N. et al. Neurochemical signs of astrocytic and neuronal injury in acute COVID-19 normalizes during long-term follow-up. EBioMedicine 70, 103512 (2021).
Article CAS PubMed PubMed Central Google Scholar
Boesl, F. et al. Cognitive decline in post-COVID-19 syndrome does not correspond with persisting neuronal or astrocytic damage. Sci. Rep. 14, 5326 (2024).
Article ADS CAS PubMed PubMed Central Google Scholar
Bonhenry, D. et al. SARS-CoV-2 infection as a cause of neurodegeneration. Lancet Neurol. 23, 562–563 (2024).
Article CAS PubMed Google Scholar
Wu, L., Arvai, S., Wang, S.-H. J., Liu, A. J. & Xu, B. Differential diagnosis of mild cognitive impairment of Alzheimer’s disease by Simoa p-tau181 measurements with matching plasma and CSF. Front. Mol. Neurosci. 16, 1288930 (2024).
Article PubMed PubMed Central Google Scholar
Blumen, H. M. et al. Cortical thickness, volume, and surface area in the motoric cognitive risk syndrome. J. Alzheimers Dis. 81, 651–665 (2021).
Article PubMed PubMed Central Google Scholar
Wisch, J. K. et al. Cross-sectional comparison of structural MRI markers of impairment in a diverse cohort of older adults. Hum. Brain Mapp. 46, e70133 (2025).
Article PubMed PubMed Central Google Scholar
Schwarz, C. G. et al. A large-scale comparison of cortical thickness and volume methods for measuring Alzheimer’s disease severity. Neuroimage Clin. 11, 802–812 (2016).
Article PubMed PubMed Central Google Scholar
Petersen, E. L. et al. Multi-organ assessment in mainly non-hospitalized individuals after SARS-CoV-2 infection: the Hamburg City Health Study COVID programme. Eur. Heart J. 43, 1124–1137 (2022).
Article CAS PubMed PubMed Central Google Scholar
Lu, Y. et al. Cerebral micro-structural changes in COVID-19 Patients - an mri-based 3-month follow-up study. EClinicalMedicine 25, 100484 (2020).
Article PubMed PubMed Central Google Scholar
Taranov, A. et al. The choroid plexus maintains adult brain ventricles and subventricular zone neuroblast pool, which facilitates poststroke neurogenesis. Proc. Natl. Acad. Sci. USA 121, e2400213121 (2024).
Article CAS PubMed PubMed Central Google Scholar
Cohen, A. D., Tomasi, D., Shokri-Kojori, E., Nencka, A. S. & Wang, Y. Functional connectivity density mapping: comparing multiband and conventional EPI protocols. Brain Imaging Behav. 12, 848–859 (2018).
Article PubMed Google Scholar
Masaldan, S., Bush, A. I., Devos, D., Rolland, A. S. & Moreau, C. Striking while the iron is hot: Iron metabolism and ferroptosis in neurodegeneration. Free Radic. Biol. Med. 133, 221–233 (2019).
Article CAS PubMed Google Scholar
Dixon, S. J. et al. Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell 149, 1060–1072 (2012).
Article CAS PubMed PubMed Central Google Scholar
Chen, X. et al. The molecular mechanisms of ferroptosis and its role in blood-brain barrier dysfunction. Front. Cell Neurosci. 16, 889765 (2022).
Article CAS PubMed PubMed Central Google Scholar
Kempuraj, D. et al. COVID-19 and long COVID: disruption of the neurovascular unit, blood-brain barrier, and tight junctions. Neuroscientist 30, 421–439 (2024).
Article CAS PubMed Google Scholar
Shackman, A. J. et al. The integration of negative affect, pain and cognitive control in the cingulate cortex. Nat. Rev. Neurosci. 12, 154–167 (2011).
Article CAS PubMed PubMed Central Google Scholar
Li, Q.-Y. et al. Neuroinflammation in the anterior cingulate cortex: the potential supraspinal mechanism underlying the mirror-image pain following motor fiber injury. J. Neuroinflamm. 19, 162 (2022).
Article CAS Google Scholar
Schneider, K. N., Sciarillo, X. A., Nudelman, J. L., Cheer, J. F. & Roesch, M. R. Anterior cingulate cortex signals attention in a social paradigm that manipulates reward and shock. Curr. Biol. 30, 3724–3735.e3722 (2020).
Article CAS PubMed PubMed Central Google Scholar
Ghersi-Egea, J.-F. et al. Molecular anatomy and functions of the choroidal blood-cerebrospinal fluid barrier in health and disease. Acta Neuropathol. 135, 337–361 (2018).
Article CAS PubMed Google Scholar
Kaur, C., Rathnasamy, G. & Ling, E.-A. The choroid plexus in healthy and diseased brain. J. Neuropathol. Exp. Neurol. 75, 198–213 (2016).
Article CAS PubMed Google Scholar
Wu, L. et al. Glymphatic system dysfunction in recovered patients with mild COVID-19: A DTI-ALPS study. iScience 27, 108647 (2024).
Shi, Q., Gutierrez, R. A. & Bhat, M. A. Microglia, Trem2, and neurodegeneration. Neuroscientist 31, 159–176 (2025).
Article CAS PubMed Google Scholar
Wu, Y. et al. TREM-2 is a sensor and activator of T cell response in SARS-CoV-2 infection. Sci. Adv. 7, eabi6802 (2021).
Article ADS CAS PubMed PubMed Central Google Scholar
Clay, M. R. & Halloran, M. C. Rho activation is apically restricted by Arhgap1 in neural crest cells and drives epithelial-to-mesenchymal transition. Development 140, 3198–3209 (2013).
Article CAS PubMed PubMed Central Google Scholar
Stankiewicz, T. R. & Linseman, D. A. Rho family GTPases: key players in neuronal development, neuronal survival, and neurodegeneration. Front. Cell Neurosci. 8, 314 (2014).
Article PubMed PubMed Central Google Scholar
Ambrogini, P. et al. Calsequestrin deletion facilitates hippocampal synaptic plasticity and spatial learning in post-natal development. Int. J. Mol. Sci. 21, 5473 (2020).
Article CAS PubMed PubMed Central Google Scholar
Martínez-Diz, S. et al. Relevance of TMPRSS2, CD163/CD206, and CD33 in clinical severity stratification of COVID-19. Front. Immunol. 13, 1094644 (2023).
Article PubMed PubMed Central Google Scholar
Saito, T., Yagi, H., Kuo, C.-W., Khoo, K.-H. & Kato, K. An embeddable molecular code for Lewis X modification through interaction with fucosyltransferase 9. Commun. Biol. 5, 676 (2022).
Article CAS PubMed PubMed Central Google Scholar
Schultheiß, C. et al. The IL-1β, IL-6, and TNF cytokine triad is associated with post-acute sequelae of COVID-19. Cell. Rep. Med. 3, 100663 (2022).
Talla, A. et al. Persistent serum protein signatures define an inflammatory subcategory of long COVID. Nat. Commun. 14, 3417 (2023).
Article ADS CAS PubMed PubMed Central Google Scholar
Lee, E.-J. et al. Ischemic stroke in patients with cancer: is it different from usual strokes?. Int J. Stroke 9, 406–412 (2014).
Article PubMed Google Scholar
Besteher, B. et al. Cortical thickness alterations and systemic inflammation define long-COVID patients with cognitive impairment. Brain Behav. Immun. 116, 175–184 (2024).
Article CAS PubMed Google Scholar
Sperling, S. et al. Fatigue is a major symptom at COVID-19 hospitalization follow-up. J. Clin. Med. 11, 2411 (2022).
Article CAS PubMed PubMed Central Google Scholar
Gross, R. & Re, V. L. Disentangling the postacute sequelae of SARS-CoV-2: E unibus pluram (from one, many). JAMA 329, 1918–1919 (2023).
Article PubMed Google Scholar
Thaweethai, T. et al. Development of a definition of postacute sequelae of SARS-CoV-2 infection. JAMA 329, 1934–1946 (2023).
Article CAS PubMed PubMed Central Google Scholar
Rubio-Rivas, M. et al. WHO ordinal scale and inflammation risk categories in COVID-19. Comparative Study of the Severity Scales. J. Gen. Intern. Med. 37, 1980–1987 (2022).
Article PubMed PubMed Central Google Scholar
Teunissen, C. E. et al. A consensus protocol for the standardization of cerebrospinal fluid collection and biobanking. Neurology 73, 1914–1922 (2009).
Article CAS PubMed PubMed Central Google Scholar
Fischl, B. et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341–355 (2002).
Article CAS PubMed Google Scholar
Fischl, B. & Dale, A. M. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc. Natl. Acad. Sci. USA 97, 11050–11055 (2000).
Article ADS CAS PubMed PubMed Central Google Scholar
Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968–980 (2006).
Article PubMed Google Scholar
Klein, A. & Tourville, J. 101 labeled brain images and a consistent human cortical labeling protocol. Front. Neurosci. 6, 171 (2012).
Article PubMed PubMed Central Google Scholar
Billot, B. et al. SynthSeg: segmentation of brain MRI scans of any contrast and resolution without retraining. Med. Image Anal. 86, 102789 (2023).
Article PubMed PubMed Central Google Scholar
Schofield, M. A. & Zhu, Y. Fast phase unwrapping algorithm for interferometric applications. Opt. Lett. 28, 1194–1196 (2003).
Article ADS PubMed Google Scholar
Tadayon, E. et al. Improving choroid plexus segmentation in the healthy and diseased brain: relevance for tau-PET imaging in dementia. J. Alzheimers Dis. 74, 1057–1068 (2020).
Article PubMed PubMed Central Google Scholar
Bae, Y. J. et al. Altered brain glymphatic flow at diffusion-tensor MRI in rapid eye movement sleep behavior disorder. Radiology 307, e221848 (2023).
Article PubMed Google Scholar
Zhang, W. et al. Glymphatic clearance function in patients with cerebral small vessel disease. Neuroimage 238, 118257 (2021).
Article PubMed Google Scholar
Taoka, T. et al. Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer’s disease cases. Jpn J. Radiol. 35, 172–178 (2017).
Article ADS PubMed Google Scholar
Tatekawa, H. et al. Improved reproducibility of diffusion tensor image analysis along the perivascular space (DTI-ALPS) index: an analysis of reorientation technique of the OASIS-3 dataset. Jpn J. Radiol. 41, 393–400 (2023).
Article PubMed Google Scholar
Smith, S. M. et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31, 1487–1505 (2006).
Article PubMed Google Scholar
Chao, Y.-P., Liu, P.-T. B., Wang, P.-N. & Cheng, C.-H. Reduced inter-voxel white matter integrity in subjective cognitive decline: diffusion tensor imaging with tract-based spatial statistics analysis. Frontl Aging Neurosci. 14, 810998 (2022).
Article Google Scholar
Thiel, K. et al. Reduced fractional anisotropy in bipolar disorder v. major depressive disorder independent of current symptoms. Psychol. Medl 53, 4592–4602 (2023).
Article Google Scholar

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This research was funded by a grant from the Korea Disease Control and Prevention Agency [grant number HD22C2045].

These authors contributed equally: Dayoung Seo, Yangsean Choi.

Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
Dayoung Seo, Sanghwi Bang, In-Hye Jang, Lynkyung Choi, Jin Hee Kim, Wangyoung Shin, Bo-Ra Seo, Shina Kim, Hee-Jae Jung, Ji-Yon Kim, Hyunjin Kim, Young-Min Lim & Eun-Jae Lee
Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Seoul, Republic of Korea
Dayoung Seo & Eunseon Jeong
Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
Yangsean Choi & Eunseon Jeong
Clinical Research Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
Ji-Sung Lee
Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
Ji-Soo Kwon, Euijin Chang & Sung-Han Kim
Department of Infectious Diseases, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
Jacob Lee
Department of Brain & Cognitive Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
Tae-In Kam
Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
Su-Hyung Park

D.S., Y.C., T.I.K., S.H.P., E.J.L., and S.H.K. conceptualized and developed the study. E.S.J., S.B., J.S.L., I.H.J., L.C., J.H.K., W.S., B.R.S., S.K., H.J.J., J.Y.K., H.K., Y.M.L., J.S.K., and E.C. performed experiments and analyzed the data. D.S., Y. C., E.J., and E.J.L. visualized the data. E.J.L., J.L., and S.H.K. acquired funding. D.S., Y. C., E.J.L., and S.H.K. performed project administration. E.J.L. and S.H.K. supervised the study. D.S., E.J.L., Y.C., and S.H.K. wrote the original draft of the manuscript. All the authors reviewed and edited the manuscript.

Correspondence to Eun-Jae Lee or Sung-Han Kim.

The authors declare no competing interests.

Nature Communications thanks Nikolaos Karvelas and the other anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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