#124 – AMA #15: Real-world case studies—metabolic dysregulation, low testosterone, menopause, and more

As a follow up to AMA #14 where Peter explained his framework for analyzing labs, this “Ask Me Anything” (AMA) episode focuses on a number of real-world case studies exploring metabolic dysregulation, low testosterone, menopause, hypothyroidism, elevated uric acid, and more. From the examples discussed, you can follow along how our clinical team goes about interpreting diagnostic measures and applying relevant research findings. Once again, Bob Kaplan, Peter’s head of research, will be asking the questions. If you’re a subscriber, you can now listen to this full episode on your private RSS feed or on our website at the AMA #15 show notes page. If you are not a subscriber, you can learn more about the subscriber benefits here.

AMA #15 Sneak Peak:

We discuss:

• Should you stop taking supplements before getting a lab test? [2:45];
• Family history—Questions to ask and what to look for [5:30];
• The purpose of an oral glucose tolerance test (OGTT) [12:15];
• Case study—Insufficient muscle mass for proper glucose disposal [17:15];
• Why hemoglobin A1c is a relatively unhelpful metric [24:00];
• Case study—Exceeding carbohydrate tolerance [26:30];
• Case study—Metabolic dysfunction and a framework for metabolic health [33:30];
• Peter’s ideal tracking of metabolic health for all his patients [43:30];
• Contrasting presentations of hypogonadism—Low free testosterone [45:00];
• How sleep, exercise, and alcohol affect testosterone levels? [56:20];
• Case study—Surprisingly fast onset of menopause [59:25];
• Case study—Hypothyroidism and high cholesterol [1:07:00];
• Case study—Elevated uric acid and hypertension [1:10:55]; and
• More.

Should you stop taking supplements before getting a lab test? [2:45]

Does Peter have patients stop taking their supplements before doing their lab tests?

• Peter actually prefers that patients ARE taking the supplements that they typically take
• In fact, he will postpone lab work to allow for a person re-continue taking a supplement that they may have run out of
• For example, if a person is taking methylated B vitamins because they have high homocysteine, we wouldn’t want to run lab tests if they ran out of their supplement — we’d want to see their labs with the supplement to make sure it’s keeping homocysteine down

The more important point: You need to know how long it takes to see the effect of the intervention

For example, one of the longer tail things is looking at omega-3 index  

• The Omega Quant test looks at the red blood cell membranes and measures the amount of EPA and DHA (Omega 3 fatty acids) 
• Your index number rises with increase fish consumption and/or taking fish oil supplements but it takes 3+ months to fully assimilate the change 
• And if you think that the change is supposed to happen quicker, you could be misled into thinking you’re not giving them enough
• By contrast, with a drug like Repatha, a few doses would be sufficient to know if the drug is working or not

⇒ See episode of The Drive with Bill Harris for more on omega-3 fatty acids

Family history—Questions to ask and what to look for [5:30]

Is 23andMe data comparable to family history data?

• “Actually, that pretty much tells me nothing . . . this stuff doesn’t mean Jack compared to your family history.”
• With the 23andME data, you CAN look at things like
  •  i)  TOMM40 gene to assess risk of Alzheimer’s disease, and/or 
  • ii) FOXO3 — a gene associated with longevity 
• But the genes Peter thinks are important are things that they measure on their own (e.g., MTHFR, APOE, etc.)

Family history data

• Peter gives new patients a large form prior to their first visit
• He wants to know everything knowable about mother, father, both sets of grandparents, aunts and uncles, and siblings
• Cardiovascular disease, for example—does anybody have a history of cardiovascular disease? Did they take any medication for blood pressure, cholesterol? Did they ever have a stroke, chest pain, heart attack?
• Same questions around dementia, cancer, metabolic disease/diabetes
• Next, they prod the answers to those questions to understand context: 
  • You may see a family history full of cancer, but then find out that they all smoked three packs a day
  • The patient may have a relative die of a heart attack at 50—Is this a case of LP(a)? Was this person an alcoholic and heavy smoker?

Looking for patterns

• The more time you spend gathering data, the more likely you’ll understand what’s really at the root of the genetic template that you inherited
• You’re looking for patterns—signature of cancer, dementia, cardiovascular disease
• Example — 
  • About 1 in 10 people show up with an elevated Lp(a), but the number by itself doesn’t tell you how bad of a problem it is
  • We know Lp(a) is bad, but is this a big problem or just a medium problem? 
  • For the patients who have family members with a lot of sub 60 year old cardiovascular events AND elevated Lp(a) — you need to be acting on that in the most aggressive manner 
  • But maybe you can afford to be less aggressive in the case where families have high Lp(a) but nobody’s having any events until their 80s

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