The Genetic Architecture Of Osteoarthritis

Genetic links between higher BMI and osteoarthritis exist. Abstract:

Osteoarthritis is a common complex disease imposing a large public-health burden. Here, we performed a genome-wide association study for osteoarthritis, using data across 16.5 million variants from the UK Biobank resource. After performing replication and meta-analysis in up to 30,727 cases and 297,191 controls, we identified nine new osteoarthritis loci, in all of which the most likely causal variant was noncoding. For three loci, we detected association with biologically relevant radiographic endophenotypes, and in five signals we identified genes that were differentially expressed in degraded compared with intact articular cartilage from patients with osteoarthritis. We established causal effects on osteoarthritis for higher body mass index but not for triglyceride levels or genetic predisposition to type 2 diabetes.

BMI, Metabolic Syndrome, And Pancreatic Cancer

Here is study linking higher BMI, and higher fasting insulin levels (metabolic syndrome, insulin resistance), with an increased risk for pancreatic cancer.  The burden of morbidity and mortality caused by overweight/obesity is staggering, something to keep in mind when reading all the popular stories on the Internet that attempt to normalize obesity and rant about “fat shaming” and “body shaming.”  Being overweight is literally killing people, why normalize it?  Abstract:

BACKGROUND:

Risk factors for pancreatic cancer include a cluster of metabolic conditions such as obesity, hypertension, dyslipidemia, insulin resistance, and type 2 diabetes. Given that these risk factors are correlated, separating out causal from confounded effects is challenging. Mendelian randomization (MR), or the use of genetic instrumental variables, may facilitate the identification of the metabolic drivers of pancreatic cancer.

METHODS:

We identified genetic instruments for obesity, body shape, dyslipidemia, insulin resistance, and type 2 diabetes in order to evaluate their causal role in pancreatic cancer etiology. These instruments were analyzed in relation to risk using a likelihood-based MR approach within a series of 7110 pancreatic cancer patients and 7264 control subjects using genome-wide data from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Potential unknown pleiotropic effects were assessed using a weighted median approach and MR-Egger sensitivity analyses.

RESULTS:

Results indicated a robust causal association of increasing body mass index (BMI) with pancreatic cancer risk (odds ratio [OR] = 1.34, 95% confidence interval [CI] = 1.09 to 1.65, for each standard deviation increase in BMI [4.6 kg/m2]). There was also evidence that genetically increased fasting insulin levels were causally associated with an increased risk of pancreatic cancer (OR = 1.66, 95% CI = 1.05 to 2.63, per SD [44.4 pmol/L]). Notably, no evidence of a causal relationship was observed for type 2 diabetes, nor for dyslipidemia. Sensitivity analyses did not indicate that pleiotropy was an important source of bias.

CONCLUSIONS:

Our results suggest a causal role of BMI and fasting insulin in pancreatic cancer etiology.

Controversy: Requiem For BMI?

By BruceBlaus - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=44922550

Look at this paper; abstract reproduced below.  Now, I agree that BMI is a flawed measure.  It always struck me as odd that the BMI cutoffs for normal vs. overweight vs. obese were the same for men and women, considering that the typical man is larger framed and more muscular than the typical woman of the same height, and would therefore weigh more even if of completely healthy body composition. BMI also does not distinguish between the 200 pound athlete with high muscularity and low bodyfat and the 200 pound coach potato who is extremely obese and unhealthy. So, in that sense, I agree with this paper. However, for the typical person at home trying to figure out how their weight fits on the healthy vs. unhealthy spectrum, BMI can be a useful, albeit flawed, measurement, especially if combined with the common sense considerations mentioned above, and also combined with a look in the mirror to ascertain how the weight is distributed.  The typical person is not going to have access to the tools to accurately measure specific body fat percentage; hence the utility of BMI + common sense + visual observation to make judgments about healthy vs. unhealthy weight.

PURPOSE OF REVIEW:Quetelet reported in the nineteenth century that body weight varies across adults with the square of height. Quetelet's index, now known as BMI, is accepted by most health organizations as a first-level measure of body fat and as a screening tool for diagnosing excess adiposity. Modern imaging methods now, however, indicate that BMI has limited predictive value for estimating body fat and lean mass at the individual level. The use of BMI as a measure of body composition in the clinical setting should therefore be challenged.RECENT FINDINGS:Recent studies enrolling cancer and surgical patients reported discrepant outcomes when BMI was used as a body composition surrogate. Sarcopenia, loss of muscle mass and function, which affects the elderly and those with chronic and acute diseases, is not accurately diagnosed with BMI. The distribution of adipose tissue is not characterized by BMI, specific measures of which have greater predictive value for metabolic impairments and clinical outcomes.SUMMARY:BMI, as the traditional tool for assessing malnutrition and obesity, is not appropriate to accurately differentiate between important body weight components and therefore should not be used for making clinically important decisions at the individual patient level.