What are the best lab tests to request from your PCP? (AMA #1)

Most PCPs will not order this test without patient request. The common objection is 'nothing can be done about a genetic marker.' Attia's counterargument: the same logic would preclude BRCA testing. Elevated Lp(a) is actionable because it justifies escalating all other cardiovascular risk interventions — lower ApoB targets, earlier CT-calcium scoring, earlier stress testing, potentially aspirin for primary prevention in high-risk genotypes. Lp(a) mass below ~30 mg/dL is generally reassuring; above 50 mg/dL is clinically significant; very high levels (>100 mg/dL) approach familial hypercholesterolemia-level risk.

ApoE2 carriers generally have lower LDL and higher triglycerides. ApoE3 is the most common 'neutral' variant. ApoE4 carriers have elevated LDL and a much higher lifetime Alzheimer's risk — E4/E4 homozygotes face approximately 30-50% lifetime risk vs ~10% for E3/E3. From a lipid standpoint, ApoE4 carriers absorb more cholesterol from the gut and clear LDL particles more slowly, making dietary saturated fat particularly impactful and ezetimibe (absorption blocker) a potentially high-leverage tool. Attia and Richard Isaacson at Cornell co-authored an Alzheimer's prevention paper specifically arguing the case for proactive genotyping and preventive intervention.

The four factors that drive ApoB level are: (1) cholesterol synthesis rate — lowered by statins and red yeast rice; (2) sterol reabsorption — lowered by ezetimibe or bile acid sequestrants; (3) triglyceride load — highly diet-sensitive, the most rapidly changeable variable; (4) LDL receptor clearance — largely genetic, boosted by PCSK9 inhibitors. Understanding which lever is dominant in a given patient explains why some people respond dramatically to a low-carb diet (triglyceride-driven) while others need a statin (synthesis-driven). The VLDL-C proxy — non-HDL-C minus LDL-C from a standard panel — is a poor man's substitute for measuring VLDL remnant burden directly; target below 15 mg/dL.

Attia's specific numeric targets are substantially more aggressive than standard clinical cutoffs: fasting glucose below 90 mg/dL (standard prediabetes threshold is 100 mg/dL), fasting insulin below 6 µU/mL, 1-hour postprandial glucose below 120-130 mg/dL (adjusted for muscle mass — more muscular people have better glucose disposal), and 2-hour glucose below 100 mg/dL with insulin below 20 µU/mL. The case patient Attia describes: fasting glucose normal, fasting insulin below 6, 1-hour glucose 114 (fine), 1-hour insulin 56 (alarming), 2-hour glucose fine, 2-hour insulin below 20. By every glucose metric this person passes. By the insulin metric at 1 hour, they are already in the early compensation phase of insulin resistance. Standard clinical guidelines would offer this patient no intervention. Attia would intervene immediately.

Attia's view on reference range drift applies broadly but is most clinically actionable for ALT. The narrative: in 2000, less than 1% of US liver transplants were for non-alcoholic fatty liver disease. By 2025 projections, the NAFLD→NASH→cirrhosis pathway will be the leading indication for liver transplant in the US — a transformation that has occurred within a single generation. The driving mechanism, per Attia and Lustig: the rise in fructose consumption causing hepatic de novo lipogenesis. Because the lab range is recalculated from population samples periodically, and because the population's average liver health has deteriorated, the 'normal' range has been silently recalibrated upward — hiding the epidemic in plain sight. The same corrupted-reference-range logic applies to fasting glucose (now set at 100 mg/dL for 'normal,' while 30 years ago it was 90), HbA1c, and estradiol in men.

Attia frames the physician refusal to test Lp(a) as fundamentally wrongheaded: the same logic — 'don't tell a patient about a genetic risk they can't fix' — would justify not testing BRCA status or not doing coronary artery calcium scoring. His counter: once a patient knows their Lp(a) is elevated, the entire cascade of downstream risk-mitigation — more aggressive LDL lowering, aspirin consideration, earlier imaging — becomes justified. Lp(a) particle number is the preferred metric; Lp(a) mass is an acceptable first-order approximation when particle number is unavailable. It only needs to be checked once in a lifetime because it is largely genetically determined and stable.

The standard physician objection to ordering ApoE genotyping is: 'I don't want to alarm a patient about a risk they cannot change.' Attia's rebuttal — published with Richard Isaacson at Cornell — is that Alzheimer's disease is at least somewhat if not significantly preventable, and that knowing your ApoE status early lets you prioritize sleep, head-injury avoidance, cardiovascular risk management, and possibly pharmacologic interventions in clinical trials. Beyond Alzheimer's, the ApoE genotype tells you enormous amounts about cardiovascular risk: E2 carriers typically have lower LDL and higher triglycerides; E4 carriers have elevated LDL that responds more to dietary saturated fat. Understanding which lipid-lowering mechanism (synthesis inhibition, reabsorption blockade, or receptor upregulation) to prioritize often flows from ApoE genotype. This is a one-time test — your genotype never changes.

Four factors drive ApoB/LDL-P: (1) the rate of cholesterol synthesis (modulated by statins, red yeast rice), (2) cholesterol and sterol reabsorption from the gut (modulated by ezetimibe), (3) the circulating triglyceride load (highly diet-sensitive — triglycerides are the most responsive lipid fraction to nutritional change), and (4) LDL receptor clearance (primarily genetic, driven by LDL-R expression in the liver, modulated by PCSK9 inhibitors). Because all four levers respond differently to diet and drugs, knowing your ApoB or LDL-P longitudinally tells you which lever is most off and which intervention to target. The preferred clinical use is to track ApoB over time with each dietary or pharmacologic change.

Attia's OGTT protocol requires measuring both glucose and insulin at fasting, 1 hour, and 2 hours after consuming 75-100g glucose (standard liquid Glu-Cola, though Attia is now increasingly using 100g of rice or potatoes as a more physiologically natural challenge). His thresholds: fasting glucose below 90 mg/dL, fasting insulin below 6 µU/mL, 1-hour postprandial glucose below 120-130 mg/dL (adjusted for muscle mass), 1-hour insulin below roughly 30 µU/mL (implied by the alarm at 56), and 2-hour glucose below 100 mg/dL with insulin below 20 µU/mL. A patient can pass every glucose threshold and still have a 1-hour insulin of 56 — which Attia describes as a harbinger 5 years ahead of clinical insulin resistance. That five-year window is precisely when intervention is most powerful.

The mechanism Attia and Lustig implicate is fructose — not dietary fat, not total calories. Fructose is metabolized almost exclusively in the liver (unlike glucose, which distributes to all tissues) and at high doses promotes de novo lipogenesis and hepatic steatosis. The reference range problem is not unique to ALT: Attia also notes he has personally witnessed two upward shifts in the normal range for estradiol in men at the same laboratory over just eight years — a direct signal that population testosterone/estrogen balance is shifting, presumably driven by environmental estrogen exposure, adiposity, and endocrine disruptors. The implication for any biomarker: 'within range' means 'within the current sick population average,' not 'optimal.'

Attia notes the causes of rising male estradiol are likely multifactorial — increased adiposity (adipose tissue aromatizes testosterone to estradiol), environmental estrogen exposure (plastics, phytoestrogens, pesticides), and possibly dietary shifts. He doesn't drill into the mechanisms in this episode, flagging it for a future dedicated discussion. The clinical takeaway is the same as with ALT: use functionally-optimal targets, not population-derived reference ranges.