This study aimed to investigate the shortcoming of BMI as a measurement of adiposity in patients with familial partial lipodystrophy (FPLD). Methods: Two different matching procedures were used to compare 55 FPLD versus control patients with severe obesity (N = 548 patients) to study the relationship between body weight, fat distribution, and metabolic diseases, such as diabetes mellitus, hypertriglyceridemia, and nonalcoholic steatohepatitis. In MATCH1, the patients with FPLD were matched to controls with obesity (OCs) by truncal mass, and in MATCH2, the patients with FPLD were matched to OCs with respect to glucose control. Results: With MATCH1, the FPLD group had worse glycemic control (hemoglobin A1c 8.2% ± 1.6% vs. 5.9% ± 0.9%), higher triglycerides (884 ± 1,190 mg/dL vs. 139 ± 79 mg/dL), and lower leptin (20.5 ± 15.8 ng/ mL vs. 41.9 ± 29.4 ng/mL, P < 0.001 for all comparisons). In MATCH2, metabolic comorbidity-matched FPLD patients had significantly lower BMI compared with OCs (29.5 ± 5.7 kg/m 2 vs. 38.6 ± 5.2 kg/m 2 , P < 0.001). Conclusions: Patients with FPLD with similar truncal mass have worse metabolic profiles than non-FPLD OCs. The differential BMI between the FPLD and OCs, when matched for their metabolic comorbidities, approximates 8.6 BMI units.

Familial partial lipodystrophy (FPLD) presents with an absence of adipose tissue in the extremities, with accumulation in the upper body. Metabolic abnormalities associated with FPLD include diabetes mellitus and/or severe insulin resistance, hypertriglyceridemia, and non-alcoholic steatohepatitis. FPLD patients have a disproportionately lower BMI compared to individuals with common obesity and similar metabolic derangements. However, the extent and degree of metabolic disease at comparable truncal mass, or the “equivalent” BMI between the groups with similar metabolic disease are not known. To determine a BMI reference or “equivalence”, we performed a retrospective case control study comparing “cases” of FPLD against “controls” with severe obesity while matching for co-morbidities or total trunk mass. Baseline data were gathered to perform two k:1 nearest neighbor case-control matches using matchControls function of R’s e1071 package. MATCH1 included matching of age, sex, and total trunk mass with the hypothesis that FPLD with similar trunk mass had worse metabolic parameters. MATCH2 was performed using age, sex, and presence of comorbidities (hypertension, hypertriglyceridemia (>300mg/dL), diabetes, fatty liver, heart disease, arthritis, depression and anxiety, smoking history) with the hypothesis that there would be a significant difference in weight or BMI between the two populations. Our populations consisted of 55 FPLD cases (46F/9M, Age = 47±12 years, Total trunk mass=45.3±11.6 Kg) and a pool of 549 non-FPLD controls (338F/211M, Age = 48±10 years). MATCH1 allowed for a 2:1 nearest neighbor match with 110 obese controls (92F/18M, p=1.00, Age=48±11 years, p=0.72; Total Trunk Mass= 46.8±10.9 Kg, p=0.36). FPLD had worse glycemic control (HbA1c= 8.2±1.6%, 5.9±0.9%, respectively, p=<0.001), higher triglycerides (884±1190 mg/dL, 139±79 mg/dL, respectively, p<0.001), and lower leptin compared to obese controls (20.5±15.8 ng/mL, 41.9±29.4 ng/mL, p<0.001). MATCH2 allowed for a 1:1 nearest neighbor match with 55 controls (38F/17M, Age=53±9 years). The two groups had similar glycemic control (HbA1c = 8.2±1.6%, 7.8±1.6%, respectively, p=0.15), but the FPLD group had markedly higher triglycerides (884±1190 mg/dL, 224±123 mg/dL, respectively, p<0.001). Average BMI was 9.1 kg/m 2 lower in the FPLD group compared to controls (BMI = 29.5±5.7 kg/m 2 , 38.6±5.2 kg/m 2 , respectively, p<0.001). In conclusion , FPLD patients with a similar truncal mass will have a worse metabolic profile than that of a non-FPLD obese patients despite having a lower BMI. This supports the understanding that lack of healthy fat depots drives metabolic disease in FPLD. The metabolic disease burden of the FPLD patients is equivalent to non-FPLD obesity that is at on average 9.1kg/m 2 heavier than the observed BMI. This can be taken into account while defining weight goals for these patie...

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