What Twenty Years of “Borderline” LDL Actually Costs You

My LDL was never the horror-show number.

That was the trap.

For most of my adult life it sat in the 130s, 140s, sometimes brushing 150. High enough to matter. Never high enough to make anyone slam a chart shut and say, “We need to deal with this now.” Starting around age thirty I got the same line at almost every visit: borderline. Watch your diet. Recheck in a year. And a statin wouldn’t be a horrible idea, but never was a full court press to get me to start one.

I should have been the patient most likely to catch this. Bioinformatics training. Fifteen years inside the supplement industry. An ER nurse and PhD/APRN student who reads the primary papers, not the blogs about the papers. I was wearing the trackers, pulling my own labs, running the diet, buying the argument that the rest of my markers looked clean so the cholesterol could wait. And not one person, including me, ever did the math that actually mattered.

Because the artery doesn’t experience LDL as a number on a printout. It experiences a running total: how high, multiplied by how long. By the time a CT angiogram found an 80% blockage in my right coronary artery, I had already paid for twenty years of “borderline” that nobody ever added up.

Here’s the part that should make you angry, because it’s the part that fooled me. The villain in this story isn’t LDL, and it isn’t cardiologists. It’s a single word, and the way the whole screening framework is built around it. “Borderline” is a label for the lab value. Exposure is what the artery lives through. Those are not the same thing, and the gap between them is where the damage hides.

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The Bottom Line A single LDL of 140 to 150 in a 35-year-old almost never gets treated like a problem, because the 10-year risk score says it isn’t one. But arteries don’t run on 10-year clocks. They log exposure year after year, and the genetics, the long-term cohorts, and the trial data all point the same way: how long you carry the number matters at least as much as the number itself.

I’m not saying every 35-year-old with an LDL of 135 needs a pill tomorrow. I’m saying “your 10-year risk is low” is an incomplete answer to a problem that unfolds over thirty years. The cheapest cardiovascular intervention I never made was the conversation I could have had at thirty.

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Vocabulary that matters

• LDL-C: the cholesterol carried inside LDL particles. The number on your standard panel. Useful, but a rough proxy.
• ApoB: a direct count of the artery-clogging particles themselves. Tracks risk better than the cholesterol number alone.
• Lp(a): a separate, mostly genetic risk particle most doctors won’t test unless you ask. Worth knowing once in your life.
• Cumulative exposure (mg-years): your LDL level multiplied by the years you’ve carried it. What your arteries have actually been absorbing, added up.
• 10-year risk: the short-term event odds the standard calculators estimate. Not the same thing as your lifetime arterial burden.

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What “borderline” actually means in current practice

The screening framework treats LDL like a thermostat reading. You walk in, get a number, and the number gets dropped into a bucket:

• Under 100: optimal
• 100 to 129: near optimal
• 130 to 159: borderline
• 160 to 189: high
• 190+: very high

The action threshold for starting a statin in someone with no prior cardiac disease usually requires LDL above 190, or LDL between 70 and 189 paired with a 10-year risk score above some cutoff, typically 7.5% to 10% depending on the guideline. The risk score does what it was built to do: estimate ten-year event odds in middle-aged adults, and it does that reasonably well. The trouble starts when it gets pointed at a thirty-five-year-old. Their 10-year risk is dominated by one variable: age. The score can’t see fifteen more years of accumulating exposure. It only sees the next ten.

So the visit goes: borderline, recheck in a year, watch your diet, see you in twelve months. The patient walks out without alarm, because in the framework’s own terms there’s no alarm to sound. That’s not a bad doctor. That’s a measurement model asking the wrong question and getting a reassuring answer to it.

And the reassurance is dangerous precisely because of how this disease tends to announce itself. For some people, sudden cardiac death is the first sign of coronary disease they ever get, with no warning symptoms beforehand.³ By the time the snapshot finally has something alarming to show you, the answer has, for too many people, already arrived. That’s the cost of treating a running total as if it were a single dot.

And the diet advice doesn’t close the gap

The dietary advice the borderline patient gets is, on average, undersized for the problem. Trials of standard cardio-protective diets, Mediterranean-style eating included, generally show modest LDL reductions in tightly controlled settings, and the effect shrinks further once you account for how real people adhere over years. More aggressive plant-forward patterns can push the number harder, though long-term adherence in diet trials falls off steeply.

None of that means diet is irrelevant. Diet matters enormously, in both directions. Keto and high-saturated-fat patterns can drive LDL up sharply in certain people, which is the argument I made in Post 2 about the keto trial that got retracted, and individual response varies wildly. The point here is narrow: the generic “eat Mediterranean and recheck in a year” advice handed to the borderline patient does not, on average, move the exposure curve at the size the math is asking for.

The cigarette analogy

Think about how we talk about a different kind of cumulative exposure. A pack a day for twenty years is twenty pack-years. No physician looks at twenty pack-years and calls the smoking “borderline.” The cumulative number is the diagnosis. Lung cancer risk, COPD risk, even smoking-attributable heart disease, all of it scales with pack-years, not with whether the patient happened to be smoking on the morning of the appointment. Pack-years live inside the medical vocabulary because the arithmetic is what predicts the outcome.

LDL works exactly the same way. The screening framework just hasn’t absorbed the arithmetic yet.

What cumulative LDL exposure actually measures

Here’s what the framework doesn’t measure. Elevated LDL damages the artery every year it’s elevated. Not in proportion to today’s level, but in proportion to the running total of that level across time. Twenty years of LDL 145 isn’t twenty data points of “borderline.” It’s a continuous buildup of ApoB-carrying particles crossing the inner wall of the artery, lodging in the lining, and kicking off the cascade that becomes plaque. The unit that captures it is mg-years: your LDL number multiplied by the years you’ve carried it. Some lipidologists call it LDL-years or mmol-years. Same idea, different label.

And here’s the part that reframes the whole thing, the part I came to appreciate late. That buildup doesn’t need an injury to get started. The older teaching was that an artery had to be damaged first, by inflammation or some other insult, before cholesterol could move in and do harm. The better-supported model is close to the reverse. The retention of ApoB particles in the wall is itself the initiating event, and in the words of the researchers who named the response-to-retention model, it is “both necessary and sufficient to provoke lesion initiation in an otherwise-normal artery.”⁶ The inflammation everyone talks about comes after, as the wall’s response to the particles it has already trapped and chemically modified, not as the ticket those particles needed to get in.⁵ That is why duration is so unforgiving. You don’t have to damage the artery first and then wait. Carry enough ApoB for enough years and the particle is the insult. (Why some walls retain more than others, the endothelium, blood pressure, the geometry of flow, is its own chapter, and it’s coming later in this series.)

A 35-year-old who has run an LDL of 145 since age 20 has already banked roughly 2,175 mg-years of exposure. Their panel today reads “borderline.” Their artery has been logging the damage since college.

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What Mendelian randomization actually shows

In 2012, Brian Ference and his colleagues published a Mendelian randomization study in the Journal of the American College of Cardiology that, for my money, is the cleanest evidence we have on the question of when mattering as much as how much.¹ With my background in bioinformatics and epidemiology, I put serious weight on this design. A well-run Mendelian randomization isn’t ordinary observational epidemiology. It’s a way to draw something close to a causal arrow from genetics to outcome.

Here’s the intuition. A regular observational study compares people who have low LDL because of something, diet, a statin, exercise, body weight, plain luck, against people with higher LDL. Pulling the LDL effect out from everything else tangled up with it is brutally hard. A Mendelian randomization study instead compares people who inherited gene variants that lower their LDL from birth, assigned by chance at conception, before they made a single lifestyle decision, against everyone else. The genetics randomize the exposure the way a clinical trial randomizes a drug, except the assignment happens at conception and runs for a lifetime. Compare carriers to non-carriers and you get something close to a randomized experiment of “what if you’d had lower LDL from birth,” without anyone ever having to run it.

Ference’s team pooled nine such variants across six genes. The meta-analysis covered 312,321 participants.

The finding: each 1 mmol/L (about 38.7 mg/dL) of genetically lower LDL was associated with a 54.5% reduction in coronary heart disease risk (95% CI 48.8% to 59.5%, p = 8.43 × 10⁻¹⁹). All nine variants pointed the same direction, with no meaningful heterogeneity.

Now set that against a statin started later in life. In Ference’s comparison with the long-running statin-trial meta-analyses, midlife treatment that achieves the same drop in the LDL number cuts coronary risk by roughly a third as much as the genetic effect. Both numbers are real. The drug works. The genetics work. They produce the same delta in the LDL number.

But the genetic version is associated with roughly three times the reduction in coronary risk per unit of LDL than a midlife statin delivers. The difference isn’t the molecule. It’s the duration. The genetic carrier ran lower LDL from conception. The midlife statin patient ran lower LDL from fifty onward. Same change in the number, different starting line on the timeline, and the timeline is where most of the damage gets done.

And the trials confirm the direction independently of the genetics. Pooling 26 randomized trials and 170,000 people, the Cholesterol Treatment Trialists found that each 1 mmol/L drop in LDL cut major vascular events by about a fifth, and found no threshold down to the lowest levels studied.⁷ Lower is better, and there’s no point on the curve where the benefit suddenly stops. Genetics, cohorts, and randomized trials all converge on the same line.

(Honest caveat: a slice of that genetic effect probably reflects vascular development, not just longer exposure. Lifetime-low LDL from conception shapes how the vasculature is built, not only how many years it’s spared. The real story is likely “more years of lower LDL plus a better-developed arterial tree,” not pure exposure-time. But the gap is far too big for development to explain on its own.)

My read: the math the framework never shows your thirty-five-year-old is the one that matters most. The benefit per unit of LDL roughly triples when the lowering starts early. Start-date is part of the dose.

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The CARDIA cohort: real-time confirmation in 4,958 humans

If Mendelian randomization gives the gene’s-eye view, the CARDIA study gives the longitudinal one. CARDIA, the Coronary Artery Risk Development in Young Adults study, enrolled 4,958 asymptomatic adults aged 18 to 30 in 1985 and 1986 and followed them for decades.

In 2020, Michael Domanski and colleagues published a CARDIA-based analysis that quantified, in real human longitudinal data, what cumulative LDL exposure does to event rates.² They computed each participant’s running total of LDL across age, essentially mg-years, and tracked cardiovascular events after age 40. Median follow-up after 40 was 16 years. There were 275 events: nonfatal coronary heart disease, stroke, transient ischemic attack, heart-failure hospitalization, cardiac revascularization, peripheral arterial intervention, or cardiovascular death.

After adjusting for sex, race, and the traditional risk factors, the analysis produced two findings worth reading slowly, because together they change how you should think about a “borderline” reading at thirty-five.

Finding one. Cumulative LDL exposure was significantly associated with event risk: hazard ratio 1.053 per 100 mg/dL × years (p < 0.0001). In plain terms, every additional 100 mg-years of accumulated LDL raised the hazard of a cardiovascular event by 5.3%, in a straight-line, dose-response fashion. No inflection point. More exposure, more risk, all the way down.

Finding two, the one most people miss. The same total exposure carried more risk when it accumulated earlier in life than when it accumulated later (HR 0.797 per mg/dL/year of slope, p = 0.045). Translated: 2,000 mg-years banked by the time you’re thirty-five is more dangerous than the same 2,000 mg-years accumulated between forty-five and sixty. The total was identical. The risk was not. The years that mattered most were the early ones.

This is what Mendelian randomization implied biologically, and CARDIA confirmed observationally. Two methods, two decades apart, pointing at the same place: time isn’t just a multiplier on LDL exposure. Time at the wrong age is a force multiplier.

Honest framing: this is one observational cohort. The methods are strong, but the design is observational and the finding wants replication. What makes me lean on it is the coherence, with Ference’s genetic data, with the young-adult hyperlipidemia work I cited in Post 6 (where cumulative exposure to even moderately high cholesterol in young adults predicted later heart disease in dose-dependent fashion),⁸ and with what we already know about how plaque actually forms. Several independent lines all point the same direction.

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What this means for a 35-year-old with LDL 145

Let me run the math three ways.

Case A. A 35-year-old whose LDL has hovered at 145 since age 20. Cumulative exposure by 35 is 15 × 145 = 2,175 mg-years. If nothing changes, by 45 they reach 25 × 145 = 3,625 mg-years.

Case B. Same patient, same LDL of 145 at 20. But at age 30, they (or their physician) take it seriously. Lifestyle plus, if needed, intervention brings LDL to 100. By 45 their cumulative exposure is 10 × 145 (ages 20 to 30) + 15 × 100 (ages 30 to 45) = 1,450 + 1,500 = 2,950 mg-years.

The difference between Case A and Case B by age 45 is 675 mg-years, about 19% lower lifetime LDL load. Apply Domanski’s hazard ratio of 1.053 per 100 mg-years and that avoided exposure works out to roughly a 30% lower hazard of cardiovascular events for Case B, before you even count the extra benefit Domanski found from acting earlier on the slope.

Case C. Same 35-year-old, but acts at 35 instead of 30. Cumulative by 45 is 15 × 145 + 10 × 100 = 2,175 + 1,000 = 3,175 mg-years. Five years later than Case B, and the delay costs about 225 mg-years, roughly a third of the savings Case B was on track to bank. Five years of “we’ll watch it” is not a neutral choice. It’s a third of the available risk reduction, walked away from.

Caveat, clearly: these numbers are illustrative, not prescriptive. Real lifetime LDL doesn’t sit flat at any value. It drifts up with age, swings with diet, gets shoved around by every event in a life. Real risk depends on dozens of variables this back-of-envelope doesn’t touch. But the direction is right, the magnitudes are plausible, and the lesson is the one the keto post and the next post both land on too: the timeline of your LDL isn’t the backdrop to your cardiac risk. It’s the main character.

One more honest point, because it’s the obvious objection and it’s a fair one. None of this is an argument that zero is the goal. The math here is a comparison between trajectories, not a tally counted down from some perfect number, and the gap between Case A and Case B is the same no matter where you start counting. This is also where LDL and blood pressure part ways. Blood pressure has a real floor: drop a systolic much below 90 and I’m helping run a code in the ER, which is exactly why, when I put borderline blood pressure through this same math, I measured exposure above a sensible reference instead of down to zero. LDL has no such floor that anyone has found in the range a human body can reach. People who inherit lifelong-low LDL don’t do worse; they have dramatically less heart disease, on the order of an 88% lower risk in one classic study of a natural gene variant that lowers LDL from birth.⁹ So lower really does look better, much further down than most people assume. What we genuinely don’t know yet is whether aggressively medicating an otherwise-healthy, low-risk person from, say, the low 70s down into the 40s is worth the drug, the cost, and the decades on it. That marginal call at the bottom of the range is unsettled. “Zero” was never the point, and neither is putting every thirty-year-old on a pill. The point is the trajectory, and how early you bend it.

The math your physician probably hasn’t shown you is this. At thirty-five, a “borderline” reading isn’t a holding pattern. It’s an unfolding cost.

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The 35-year window

Most cardiology screening tools, the old ASCVD risk score, the Framingham equation, QRISK, were built for people in their fifties. They estimate ten-year event risk from the traditional factors, and they’re reasonably good at telling a fifty-five-year-old whether to start a statin.

They’re the wrong tool for a thirty-five-year-old.

A thirty-five-year-old’s ten-year risk is dominated by age. The score almost always comes back low, because the next ten years (35 to 45) genuinely don’t carry much absolute event risk. But the next thirty years, the stretch where Mendelian randomization and CARDIA both say the most damage compounds, are nowhere on the score’s clock.

The right question for a thirty-five-year-old isn’t “what’s my ten-year risk?” It’s “what’s my thirty-year exposure trajectory, and what’s the payoff of acting now versus in fifteen years?” Ference and Domanski both answer the second question the same way: a lot.

This is the leverage window. It’s also the window where most people with borderline numbers do nothing, because the screening tools tell them they don’t have to.

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The guidelines are moving toward the clock. The exam room hasn’t caught up.

Here’s the encouraging part, and the reason this post isn’t an attack on cardiology. The field is already moving in this direction.

In March 2026, the ACC, the AHA, and nine other societies released the first full rewrite of the US cholesterol guideline since 2018.⁴ A few changes matter for anyone reading this with an LDL in the 130s or 140s. The guideline swaps the old Pooled Cohort risk equation for a newer calculator called PREVENT, and for the first time it explicitly endorses estimating 30-year risk alongside the 10-year number. It lowers the bar for considering LDL-lowering therapy, calling it reasonable at a borderline 10-year risk of just 3% to under 5%. It recommends measuring ApoB to catch the residual risk a plain LDL number misses. And it says Lp(a) should be measured at least once in adulthood, the genetic particle most patients have never heard of and most doctors don’t order by default.

That’s the system inching toward the math. A 30-year horizon and a one-time Lp(a) are exactly the tools a thirty-five-year-old needs.

But two honest caveats keep this from being a victory lap. First, even the 2026 guideline stops short of treating cumulative exposure, the mg-years running total, as a formal metric you track over time. It moved the horizon out to thirty years; it didn’t adopt the odometer. Second, and this is the bigger one: a guideline update does not change the exam-room conversation. A thirty-five-year-old can still walk in, hear “borderline,” and leave thinking the number is basically fine. The guideline is the manual. The conversation is what the patient actually lives, and the conversation lags the manual by years.

My read: the guidelines are catching up to the biology faster than the clinic is catching up to the guidelines. Don’t wait for either one to start the conversation for you.

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What I Changed

This is what I do now, offered as my read of the evidence and my own situation, not a prescription for yours.

I stopped asking whether my LDL was “borderline.” It’s the wrong question. I ask what my ApoB and my LDL trajectory look like over time, and I had my Lp(a) measured once so I’d know the card I was dealt.

I stopped treating a clean glucose panel, low hsCRP, decent triglycerides, and a hard training habit as proof that my LDL exposure didn’t count. That was the exact bargain that let me ignore the number for two decades. Metabolic health is real and worth having. It is not a shield against the arithmetic.

And I stopped thinking about lipids as a this-year decision. They’re a time decision. The earlier you bend the slope, the less your arteries have to carry for the rest of your life, and the years you give back to inaction are the ones you can’t buy back later.

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The conversation I wish I’d had at thirty

If I could hand my thirty-year-old self one thing, it wouldn’t be a prescription. It would be a better question to bring into the room. The system rewards the patient who walks in with the full picture and asks for what it actually warrants, the same lesson I learned fighting to get the right cardiac scan.

“I understand my 10-year risk is probably low. What I want to understand is my lifetime exposure. Can we look at my LDL-C trend, my ApoB, a one-time Lp(a), my blood pressure trend, and my family history together, and talk honestly about whether my current trajectory is acceptable over the next twenty or thirty years?”

That question does something a demand for a specific drug never could. It moves the visit from “is the number high enough today” to “is the trajectory acceptable over time,” and it forces even a physician who’s never thought in mg-years to engage you on the curve instead of the dot. If your borderline number has been borderline for ten years already, that’s not “monitor and recheck.” That’s data. Bring the time series. Twelve readings of LDL 145 over fifteen years isn’t a borderline finding. It’s a confirmed exposure pattern, and your doctor’s instinct will be to look only at the most recent point. Make sure they see the whole line.

When I look at my own labs from age 30 to 43, the mg-year arithmetic explains more of the timeline than I’m comfortable with. The conversations I could have had at thirty would have been the cheapest cardiovascular intervention I ever made. None of them happened, because nothing in the framework gave anyone, including me, a reason to think they were urgent.

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The Calibrated Claim Audit

Claim	Mechanism strength	Evidence quality	My read
“Borderline LDL is fine if your 10-year risk is low.”	Misses lifetime exposure entirely	Weak for young adults	Low short-term risk is not low lifetime burden
Cumulative LDL/ApoB exposure drives heart disease over decades.	Very strong	Strong: mechanism, genetics, cohorts, trials	High confidence. Duration is part of the dose
Lowering LDL earlier beats lowering it later.	Strong	Strong direction (Ference + CARDIA); exact size varies	Early slope changes buy years you can’t get back

Commercial distortion risk: Moderate. The foundational LDL biology isn’t a sector, but the diet, supplement, and optimization ecosystem sells “metabolically healthy” as if it cancels lipid exposure. That doesn’t make low-carb wrong. It makes the LDL caveats very easy to ignore, which is exactly what I did for twenty years.

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The Final Signal

• What this gets right. A single LDL in the 130s or 140s rarely looks dramatic on a lab report, and the 10-year math agrees. Both are reading the wrong window.
• What gets oversold. That a clean metabolic panel, a good diet, or a training habit buys you out of cumulative lipid exposure. It doesn’t. The arithmetic runs underneath all of it.
• What I changed. I track ApoB and my LDL trajectory instead of a single “borderline” snapshot, measured my Lp(a) once, and started treating lipids as a time decision, not a this-year one.
• What the system is doing. The 2026 guideline is moving toward the clock, 30-year risk, one-time Lp(a), ApoB, earlier treatment. The exam-room conversation is still years behind it. Don’t wait for it to start the conversation for you.
• What this opens next. LDL is one input. Next week I put the other “borderline” number I underestimated, blood pressure, through the same exposure math, including what the SPRINT trial actually said about numbers most of primary care still calls “not horrible.” The exposure math explains more of my own timeline than I wanted it to. It doesn’t explain all of it, and that gap is where the next few posts go.

More to come next week.

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References

1. Ference BA, Yoo W, Alesh I, Mahajan N, Mirowska KK, Mewada A, Kahn J, Afonso L, Williams KA Sr, Flack JM. Effect of long-term exposure to lower low-density lipoprotein cholesterol beginning early in life on the risk of coronary heart disease: a Mendelian randomization analysis. J Am Coll Cardiol. 2012;60(25):2631-2639. PMID: 23083789 [Finding: Across 312,321 people, each 1 mmol/L of genetically lower lifelong LDL was associated with a 54.5% lower risk of coronary heart disease, roughly three times the benefit of the same LDL drop from a statin started in midlife. The gap reflects duration of exposure, not the drug.]

2. Domanski MJ, Tian X, Wu CO, et al. Time Course of LDL Cholesterol Exposure and Cardiovascular Disease Event Risk. J Am Coll Cardiol. 2020;76(13):1507-1516. PMID: 32972526 [Finding: In 4,958 adults followed from young adulthood, cumulative LDL exposure (the area under the LDL-by-age curve) predicted later cardiovascular events. The same amount of exposure accumulated earlier in life carried more risk than the same amount accumulated later.]

3. Myerburg RJ, Junttila MJ. Sudden cardiac death caused by coronary heart disease. Circulation. 2012;125(8):1043-1052. PMID: 22371442 [Finding: A review of sudden cardiac death from coronary disease, including the well-documented pattern that sudden death can be the first clinical sign of coronary disease in people who had no prior symptoms.]

4. Writing Committee Members. 2026 ACC/AHA/AACVPR/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Dyslipidemia: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2026;153(17):e1154-e1276. PMID: 41824552 [Finding: The guideline that replaces the 2018 cholesterol guideline. It adopts the PREVENT equations for both 10- and 30-year risk, recommends ApoB and a one-time Lp(a) measurement, and lowers the threshold for considering LDL-lowering therapy in younger adults.]

5. Borén J, Chapman MJ, Krauss RM, et al. Low-density lipoproteins cause atherosclerotic cardiovascular disease: pathophysiological, genetic, and therapeutic insights: a consensus statement from the European Atherosclerosis Society Consensus Panel. Eur Heart J. 2020;41(24):2313-2330. PMID: 32052833 [Finding: An EAS consensus concluding that LDL is causal in atherosclerosis and that retention of LDL in the artery wall initiates and propagates plaque, with inflammation arising as the wall's response to the retained and modified particles.]

6. Williams KJ, Tabas I. The response-to-retention hypothesis of early atherogenesis. Arterioscler Thromb Vasc Biol. 1995;15(5):551-561. PMID: 7749869 [Finding: The paper that introduced the response-to-retention hypothesis, arguing that subendothelial retention of ApoB-containing lipoproteins is both necessary and sufficient to initiate atherosclerosis in an otherwise-normal artery, with inflammation following as a consequence.]

7. Cholesterol Treatment Trialists’ (CTT) Collaboration; Baigent C, Blackwell L, Emberson J, et al. Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet. 2010;376(9753):1670-1681. PMID: 21067804 [Finding: Pooling 170,000 people across 26 statin trials, each 1 mmol/L reduction in LDL lowered major vascular events by about a fifth. The benefit continued down to the lowest LDL levels studied, with no apparent threshold.]

8. Navar-Boggan AM, Peterson ED, D’Agostino RB Sr, Neely B, Sniderman AD, Pencina MJ. Hyperlipidemia in early adulthood increases long-term risk of coronary heart disease. Circulation. 2015;131(5):451-458. PMID: 25623155 [Finding: In the Framingham Offspring cohort, longer cumulative exposure to elevated cholesterol during young adulthood predicted higher later coronary heart disease risk in a dose-dependent way, even after accounting for cholesterol level at age 55.]

9. Cohen JC, Boerwinkle E, Mosley TH Jr, Hobbs HH. Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N Engl J Med. 2006;354(12):1264-1272. PMID: 16554528 [Finding: People carrying a natural PCSK9 gene variant that lowers LDL from birth had much less coronary heart disease, an 88% lower risk in carriers of nonsense mutations (28% lower LDL). Lifelong lower LDL, even moderately lower, tracks with substantially fewer cardiac events.]