GENERAL MEDICAL LITERATURE REVIEW
We present commentaries in this section on a broad survey of recent articles in the English literature. Articles are primarily chosen for two reasons: their potential translational value for immediate clinical practice or their ability to help determine where clinical practice might evolve in the future. Today’s topics are of general medical interest but have clear relevance to reproductive medicine.
How Lab Tests Can Be Misleading by Relying on Population-Based Reference Values
Returning once again to Eric Topol’s Ground Truth, in his December 14, 2024, posting (1), he addressed a topic in clinical medicine that probably applies to reproductive medicine more than any other specialty: the much-too-common reliance on population-based reference ranges for blood tests. A subject previously discussed in these pages, reproductive hormones for individual patients are not adequately reflected in the "normal" ranges that laboratories often publish, as what is considered normal changes significantly with age. General population-based age ranges, in contrast, group all age categories together in one large pool, and therefore do not provide age-specific levels.
In his posting, Topol specifically addressed a recent paper in Nature magazine, which used CBC data (the most frequently obtained lab test, with over 2 million tests processed per day – or 500 million per year) (2). The reasons why population-based reference values are not reliable are, in this case, somewhat different: The investigators discovered that 9 indices of a CBC had remained quite stable over 20 years, fluctuating within a very narrow range, thus demonstrating a very low coefficient of variation (CV). Indeed, inter-individual variation was far greater than intra-individual variation for each of the CBC metrics, and long-term (15+ years) variation at the individual level was similar to short-term variations (see Figure below).
The paper then explored how mortality for all causes in a large study population could be predicted based on these 9 setpoints of a CBC. Once again, the Figure below reflects the very interesting results: For predicting all-cause mortality risk, individual setpoints (shown in orange) performed significantly better than population-level reference levels (shown in blue). In fact, 20% of the cohort had an increased risk (up to 5%) of dying in the next 10 years, a partitioning that could help differentiate high-risk patients for more intensive surveillance and prevention (1).
Moreover, many of the setpoints showed associations with diseases: Red cell distribution width (RDW) with atrial fibrillation; hematocrit (HCT) with chronic kidney disease; white blood cell count (WBC) with Type 2 diabetes; mean corpuscular hemoglobin concentration (MCHC) with major adverse cardiovascular events; red blood cell count (RBC) with myelodysplastic syndrome (MDS); and mean corpuscular volume (MCV) with osteoporosis. There was also consistency in the direction and magnitude of hazard (whether up or down) for most of these associations between the two tested cohorts (see Figure below) (1).
Topol also pointed out that AI has not yet been applied in the current study to interrogate an individual’s setpoints. Such studies, such as examining lab test trends for pancreatic cancer (like bilirubin, even within the normal range), have already been suggested as indicative of higher risk – even though pancreatic cancer is rarely diagnosed at early stages.
One can easily imagine the kind of prognostic diagnostic information that AI will be able to generate for medicine from the vast data sets now available!
References
1. Topol E. Ground Truth. December 14, 2024. https://erictopol.substack.com/p/your-lab-tests
2. Foy et al., Nature 2024. December 11, 2024.. doi: 10.1038/s41586-024-08264-5. Online ahead of print.
Why Are Autoimmune Diseases Surging?
A recent article by Andrew Wang, MD, PhD, in Healio attempted to address this question (1). He noted that approximately 24 million Americans (roughly 5%) are affected by autoimmune diseases, with 8 million suffering from psoriasis, 4 million from Sjögren’s syndrome, and 3 million from inflammatory bowel disease. In the U.K., estimates are even higher – approximately 1 in 10 people. In less than 30 years, the prevalence of positive ANA tests in the U.S. has increased by almost 50%. This is, of course, highly relevant to reproductive medicine because it means more infertile and pregnant women are affected by autoimmunity.
The reasons behind this clear increase are not entirely clear. As is widely discussed today, U.S. nutrition and environmental factors are often cited, but autoimmunity is now widely regarded as having a polygenic inheritance pattern, which is highly familial, though environmental and epigenetic factors control which autoimmune disease will manifest in a given individual.
Another reason, according to the article, is that many different pathways can lead to autoimmunity. Causality is therefore difficult to establish. Consequently, the etiologies of individual autoimmune diseases remain mostly unclear, and there is growing consensus around the concept of a “multi-hit hypothesis,” involving genetic susceptibility, stress, and poor diets.
Stress appears to primarily affect the body through IL-6, the dominant cytokine associated with anxiety and depression—two conditions that have exploded in prevalence in recent years. This, and more, is discussed in Wang’s article, which is definitely worth reading.
References
Wong A. Healio. March 25, 2024. https://www.healio.com/news/rheumatology/20240321/source-of-surging-autoimmunity-may-lie-i-a-thousand-cuts