The utility of DXA and MRI for overcoming the limitations of clinical evaluation in diagnosis of partial lipodystrophy in Chinese men with metabolic syndrome: a case series

The utility of DXA and MRI for overcoming the limitations of clinical evaluation in diagnosis of partial lipodystrophy in Chinese men with metabolic syndrome: a case series | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report The utility of DXA and MRI for overcoming the limitations of clinical evaluation in diagnosis of partial lipodystrophy in Chinese men with metabolic syndrome: a case series Joan Khoo, Suresh Anand Sadananthan, Jadegoud Yaligar, Sambasivam Sendhil Velan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6756323/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background : Lipodystrophy, characterized by loss of subcutaneous adipose tissue (SAT) in the limbs, is associated with visceral adiposity and metabolic syndrome. The diagnosis of partial lipodystrophy, with fat loss affecting the legs in the presence of increased abdominal adiposity, is challenging in males due to lack of established criteria and difficulty in differentiating from the normal android pattern of obesity, especially with increasing age. There is a paucity of data in Asian populations, in whom the prevalence of diabetes is increasing and in whom lipodystrophy may be under-recognized. Methods : We describe three men (cases) of Chinese ethnicity and metabolic syndrome with clinical features suspicious of partial lipodystrophy (abdominal obesity and relatively thin lower limbs) who tested negative for Cushing syndrome, and compared their skinfold thickness and other anthropometric measurements, metabolic profile, and body composition using dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI), to a control (an abdominally obese Chinese man of similar age and BMI with metabolic syndrome). Results : The cases (age 50-51) were borderline obese by BMI (28-30 kg/m2) and abdominally obese (waist circumference WC 98-122 cm) The control was 56 years old with BMI of 31.7 kg/m2 and WC 109 cm. Despite lower BMI of the cases compared to the control, these men had more severe insulin resistance and cardiometabolic outcomes, thinner lower limb skinfolds indicating less subcutaneous fat) higher Android/Gynoid fat ratio (a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome), trunk to leg fat mass ratio and ratio of trunk to leg fat percentage (FMR) on DXA, and larger visceral abdominal fat (VAT) depots in association with more pronounced subcutaneous fat wasting in the limbs (higher VAT-to-SAT ratio) on MRI. All cases tested negative for pathogenic variants in monogenic diabetes genes. Conclusions : Our report illustrates the differences in body composition in Chinese men with clinical features of partial lipodystrophy in reference to a control of similar age and BMI. DXA and MRI are useful to characterize adiposity distribution and muscle wasting, and are useful adjunct tools for the diagnosis of partial lipodystrophy in Chinese men with metabolic syndrome. lipodystrophy metabolic syndrome DEXA MRI case report Figures Figure 1 Introduction Lipodystrophies are a heterogeneous group of congenital and acquired disorders with either partial or generalized loss of into subcutaneous adipose tissue (SAT) [ 1 – 3 ]. This atypical distribution of adiposity and reduced capacity of subcutaneous lipid storage leads to insulin resistance, inflammation, dysregulation in adipokine secretion and ectopic fat accumulation, resulting in type 2 diabetes (T2DM), fatty liver disease and other metabolic comorbidities, leading to significant morbidity and premature mortality [ 4 – 11 ]. In partial forms, fat loss affects particularly the lower limbs and instead adipose tissue may accumulate in the abdomen, face and neck. There is currently no clear consensus on clinical or imaging criteria for diagnosis of partial lipodystrophy [ 2 , 7 ]. Moreover, individuals of different ethnicity with similar BMI have different metabolic profiles due to variation in degree of abdominal (visceral) adiposity and muscle mass: in particular, East Asian (Chinese, Japanese, Korean) adults have a higher percentage of visceral fat and a more deleterious cardiometabolic risk profile compared to white Europeans, despite having a lower BMI [ 12 ]. While the reported prevalence of lipodystrophy ranges from 1.3–4.7 per million based on electronic medical record databases in the UK and USA and the prevalence of lipodystrophy is about 2.63 per million in Europe [ 3 ], there ais a paucity of data in Asian populations in whom lipodystrophy is likely under-recognized [ 3 – 5 ]. Although partial lipodystrophies appear to be more detrimental to women compared to men [ 4 , 5 , 8 , 9 ], males with partial lipodystrophy syndromes are also at increased risk of metabolic complications. In this report, we describe clinical features, metabolic profile and cardiovascular outcomes in men of East Asian (Chinese) descent with metabolic syndrome and similar BMI in the overweight/obese range, three of whom (cases) had features suggestive of partial lipodystrophy of the legs. Skinfold thickness measurements and body composition analysis using DXA and MRI scan were used to compare the cases with a control of the same ethnic group with similar age and BMI who also presented with metabolic syndrome and self-reported leg wasting, with the aim of elucidating differences in visceral and subcutaneous fat distribution to aid in the diagnosis of partial lipodystrophy. Methods Participants We studied three cases of Chinese men with similar BMI of 28-30 kg/m 2 with features suggesting partial lipodystrophy, who were managed in the endocrinology clinic of Changi General Hospital in Singapore, a Southeast Asian country with a predominantly ethnic Chinese population. For comparison, we recruited a fourth Chinese man as a ‘control’ with normal android body fat distribution and recent weight gain. The cases were initially suspected to have partial lipodystrophy based on the presence of preferential and symmetrical fat loss of the legs, with normal or increased distribution of fat on the face, neck and trunk. All patients underwent extensive history taking, physical examination and investigations to exclude endogenous and exogenous Cushing’s syndrome, human immunodeficiency virus infection, anti-retroviral therapy and cancer. This study was approved by the SingHealth Institutional Review Board ((protocol code 2015-2310 and date of approval 28th April 2015). All study participants provided written informed consent. Skinfold measurement and bioelectrical impedance analysis A 7-site skinfold measurement using Harpenden calipers were performed at these body sites: triceps, biceps, subscapular, suprailiac (otherwise known as supraspinale), abdomen, thigh, and calf of the right side of the body, as described in the international standards for anthropometric assessment, recommended by the International Society for the Advancement of Kinanthropometry [13]. To minimise inter-observer variability, skinfold readings at each of the seven sites were done by one trained personnel and averaged. Bioelectrical impedance analysis (BIA) was performed with the Tanita body composition analyser. Laboratory and genetic testing Fasting venous blood samples were taken for measurement of serum total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol concentrations (LDL-C), glucose and insulin as previously described [8]. The homeostasis model assessment index of insulin resistance (HOMA-IR) was calculated from glucose (mmol/L) x insulin (mU/L)/22.5. In Cases 2 and 3, extensive genetic testing was performed using whole genome sequencing for monogenic causes of FPLD, obesity, diabetes, severe hypertriglyceridemia, and severe insulin resistance as previously described [8]. In Case 1, the genetic panel was tested using massively parallel targeted-gene sequencing for 16 MODY- and lipodystrophy-associated genes that included PPARy and LMNA. Dual-energy X-ray absorptiometry (DXA) and MRI DXA scans were performed using Hologic QDR 4500A, fan-beam densitometer (Hologic, Inc., Bedford, Massachusetts, software version 8.21) to measure whole body composition, as previously described [8]. Including fat of total body, head, trunk, arms and legs, abdominal visceral adipose tissue (VAT), android and gynoid fat masses, and trunk to leg % fat ratio (FMR). Android and gynoid (A/G) regions were defined by the Hologic APEX software used in the scan analysis. The A/G ratio is a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome [14]. g term precision QC monitoring on phantoms for three years on the Hologic densitometer was 0.01%. Whole body MRI was performed using Siemens Prisma 3T MR scanner, except for Case 3 with implantable cardioverter defibrillator who used Siemens Sola 1.5T MR scanner. Dixon fat-water imaging sequences were used in abdominal MRI to quantify deep subcutaneous adipose tissue (DSAT), superficial subcutaneous adipose tissue (SSAT), intraperitoneal adipose tissue (IPAT), retroperitoneal adipose tissue (RPAT), and paraspinal adipose tissue (PSAT) between L1 and L5 vertebrae [14]. The mean proton density fat fraction (PDFF) were determined from the multi-echo Dixon fat-water imaging sequence and quantified as from ROIs selected within liver, pancreas, and thigh and calf muscles [8]. The intramyocellular (IMCL) and extramyocellular (EMCL) lipids within the soleus muscle were determined using magnetic resonance spectroscopy (MRS) [15]. The IMCL and EMCLwere expressed as a ratio with respect to water. Case presentations Case 1 – Partial lipodystrophy features and poorly controlled diabetes He was diagnosed with type 2 diabetes at age 40 when he presented with osmotic symptoms. His diabetes was initially well-controlled (HbA1c 7%) with increasing doses of oral glucose-lowering medications (OGLD) but gradually worsening glycaemic control requiring addition of insulin glargine at age 45. His HbA1c ranged from 10-12% for the next 5 years, despite steadily increasing insulin doses, leading to referral at age 50 to an endocrinologist who observed that he had acanthosis nigricans, abdominal adiposity, and relatively thin thighs. The limb wasting was atypical for diabetic amyotrophy, being painless and not associated with muscular weakness. There was a history of diabetes on the paternal side of the family and he suspected that some male and female paternal cousins had similar limb wasting with truncal obesity, though this was difficult to confirm as they were not on follow-up in our institution. His weight was 84.5 kg (BMI 28.2 kg/m 2 ), and anthropometric measurements revealed very low thigh skinfold thickness at 8.5 mm (Table 1), with subcutaneous fat loss and preserved muscle mass in his limbs confirmed on DXA and MRI scans (Figure 1). In contrast, he had a relatively high volume of truncal fat with A/G ratio 1.61, VAT/SAT ratio 1.42, trunk: leg fat ratio 2.07 (99th percentile for sex and age compared to men in Singapore [16]) and high ratio of trunk fat percentage to leg fat percentage (fat mass ratio, FMR) of 1.70 (above 90th percentile [16]) as well as high liver and pancreas PDFF (Table 1) on MRI, indicating significant greater visceral adiposity as a proportion of total body fat. Genetic testing was negative for monogenic diabetes of young onset (MODY) and the major lipodystrophy genes PPARY and LMNA. He was informed of the likely diagnosis of partial lipodystrophy and increased risk of metabolic complications. This diagnosis motivated him to adhere to diet, exercise and medications, with subsequent improvement of HbA1c to 7.9%. He was counselled to advise his cousins to consult their physicians regarding evaluation for lipodystrophy. Case 2 –- Partial lipodystrophy features and long-standing diabetes with microvascular and macrovascular complications He was diagnosed with diabetes at the age of 35, with a strong family history of type 2 diabetes (both parents, two siblings, maternal grandparents and cousins). Over the decade following his diagnosis, his glycaemic control progressively worsened, complicated by diabetic nephropathy, proliferative retinopathy, peripheral vascular disease and gangrene necessitating amputation of three toes on his right foot. During admission at age 50 for osteomyelitis of his right foot, he was noted during endocrinology review (for optimization of glycaemic control) to have relatively slim lower limbs in comparison to central obesity (waist circumference of 110 cm, weight 95 kg, BMI 30.6 kg/m 2 ), and acanthosis nigricans in the axillary region. On examination, there was paucity of subcutaneous fat, with a thigh skinfold thickness 19.2 mm and calf skinfold thickness 18.9 mm (Table 1). This relatively large volume of visceral trunk compared to subcutaneous (limb) adipose tissue was confirmed on DXA bioimpedance analysis by a very high trunk to leg fat ratio of 1.53 (99th percentile for sex and age) [16], A/G ratio 1.43 and FMR 1.30 (above 50th percentile [16]) (Figure 1). His MRI also demonstrated very high visceral fat content with relatively low thigh and calf SAT volumes with VAT/SAT ratio 1.88, and elevated liver and pancreas PDFF. Despite being adherent to high doses of premix insulin, his glycaemic control was poor, with HbA1c ranging from 8.4-10%, and he was changed to a basal-bolus regime with improvement in HbA1c. He was not keen for prescription of liraglutide due to the cost. While genetic testing was negative for all monogenic mutations of familial lipodystrophy syndromes, obesity, severe insulin resistance and MODY, he was advised of the clinical diagnosis of partial lipodystrophy, and to ask his family members with diabetes if they had noticed increasing abdominal girth or limb wasting. Case 3 – Severe wasting of lower limb adiposity and muscles with increased abdominal adiposity and cardiomyopathy He was hospitalised for newly-diagnosed heart failure at age 50 and found to have dilated cardiomyopathy (left ventricular ejection fraction 35%) with normal coronary arteries on angiogram. He had never smoked nor drunk alcohol and did not have diabetes, but was found to have dyslipidaemia and hypertension. There was no family history of diabetes. He had been steadily gaining weight in the last 10 year despite efforts at diet and exercise, with maximum weight at the time of admission. Physical examination revealed acanthosis nigricans and significant abdominal obesity (weight 94.2 kg, BMI 30.5 kg/m 2 , waist circumference 122 cm), which did not decrease significantly after weight loss with diuresis. Despite his weight, he had incongruously little fat in his legs, particularly in the lower leg (reduced calf skinfold thickness 11.9 mm, the lowest of all 3 cases), raising the suspicion of partial lipodystrophy. His KöB index (subscapular/calf skinfold ratio, a measure of relative subcutaneous fat in upper:lower limbs) of 2.69 was the highest of the 3 patients (Table 1), consistent with more severe wasting of subcutaneous fat in the legs. He had the lowest limb lean mass (thigh and calf muscle) volume of the 3 cases (Table 1), with MRI confirmation of the presence of severe muscle loss in addition to subcutaneous adipose tissue wasting in his legs (Table 1, Figure 1). In particular, he had fatty infiltration of thigh and calf muscles, as evidenced by high PDFF and intra- and extra-myocellular lipid accumulation on MRI (Figure 1). History and investigations were negative for endogenous or exogenous Cushing’s syndrome. Genetic testing was negative for monogenic mutations of familial lipodystrophy, obesity, severe insulin resistance and MODY. He was advised of the clinical diagnosis of partial lipodystrophy and agreed to start liraglutide, after which his weight decreased to 85 kg (11.1% reduction from baseline) and waist circumference decreased by 7 cm, though exercise was limited by cardiac dysfunction. He eventually required an implantable cardioverter defibrillator due to recurrent ventricular tachycardia which was unresponsive to medical therapy and led to sudden cardiac death at age 54. Control – android pattern of central obesity, muscle mass and metabolic profile improved with lifestyle changes He was a 56-year-old man at the time of referral to the endocrinology clinic, whose weight had increased from 80 kg to 95 kg (BMI 31.7 kg/m 2 ) over two years due to increased food intake from delivery platforms, and gym closures and lockdowns during the CoviD-19 pandemic. His waist circumference had also increased from 100cm to 109 cm, in association with self-reported reduction in his limb muscle bulk. However, in contrast to the 3 cases, his total body fat mass measured with BIA was lower, despite similar or higher thigh and calf skinfold thicknesses suggesting more lower limb subcutaneous fat. Despite higher BMI and age, his total body fat percentage was lower at 19.3% than the other three whose fat percentage ranged from 24.9 to 44.7% (Table 1), and his visceral and subcutaneous adipose tissue volumes within the expected range for men his age (T- and Z-scores 0.9 and 1.5 on DXA), in contrast to the 3 cases. Likewise, his A/G ratio 1.21 and VAT/SAT ratio 1.10 were within the normal ranges for Singapore men [16], and his trunk: leg fat ratio and FMR were lower than the cases (Table 1). With improved adherence to diet and increased exercise he lost 9 kg, reduced his waist circumference by 7 cm, and his blood pressure and serum triglycerides reduced to normal levels without the use of medications, as well as. increased arm and leg muscle mass. Table 1 : Anthropometry, metabolic features and body composition measured with skinfold calipers, bioimpedance and DXA, of four men with features of lipodystrophy. OGLD = oral glucose-lowering drugs. BIA = biolelectrical impedance analysis. Fat % trunk to fat % leg ratio = percentage of fat in trunk divided by percentage of fat in leg. The A/G ratio is a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome. FMR = fat mass ratio (ratio of trunk fat percentage to leg fat percentage). Case 1 Case 2 Case 3 Control Age 51 50 51 56 Ethnicity Chinese Chinese Chinese Chinese Hypertension Yes Yes Yes Yes Hypertriglyceridaemia Yes Yes Yes Yes Diabetes (age at diagnosis) Yes (40) Yes (35) No No Diabetes treatment OGLD Insulin - - HOMA-IR at evaluation 9.27 Not done 4.09 4.03 Anthropometry BMI (kg/m 2 ) 28.2 30.6 30.5 31.7 Waist circumference (cm) 98 110 122 109 Subscapular skinfold (mm) 37.8 29.2 32 36.2 Thigh skinfold (mm) 8.5 19.2 22.8 26.9 Calf skinfold (mm) 20.0 18.9 11.9 20.5 Subscapular to thigh skinfold ratio 4.45 1.52 1.40 1.35 Suprailiac to thigh skinfold ratio 3.46 2.02 1.74 1.41 KöB index (subscapular/calf skinfold ratio) 1.89 1.55 2.69 1.77 Body fat mass (kg) by BIA 21.0 27.8 42.1 18.3 DXA Body fat percentage (total) 24.9 27.9 44.7 19.3 Total lean mass/height 2 18.1 19.4 16.5 20.3 Abdominal VAT volume (cm 3 ) 1250 1739 1718 1235 Android to gynoid (A/G) ratio 1.61 1.43 1.25 1.21 Right leg fat mass (g) 2737.8 4925.5 4616.6 5249.2 Right leg lean mass (g) 9248.9 9749.5 7166.8 9538.5 Trunk/leg fat mass ratio 2.07 1.53 1.90 1.25 % fat trunk to % fat leg ratio (FMR) 1.70 1.30 1.20 1.11 Table 2. MRI features of adipose tissue distribution and muscle of four men with metabolic syndrome and features of lipodystrophy. SAT = subcutaneous adipose tissue. VAT = visceral adipose tissue. IMAT = intramuscular adipose tissue. PDFF: proton density fat fraction. IMCL=Intramyocellular lipids (%); EMCL=Extramyocellular lipids (%) expressed as a ratio with respect to water. Case 1 Case 2 Case 3 Control Abdominal adiposity volume Abdominal SAT (cc) 3345.3 3690.3 5404.1 3860.3 Abdominal superficial SAT (cc) 1706.4 2180.4 1991.9 2098.3 Abdominal deep SAT (cc) 1638.8 1509.2 3411.8 1761.1 Abdominal VAT (cc) 4766.7 6944.6 6559.9 4256.9 Abdominal VAT/SAT ratio 1.42 1.88 1.21 1.10 Intraperitoneal adipose tissue (cc) 3158.5 3842.4 3910.9 2336.4 Retroperitoneal adipose tissue (cc) 1459.2 2964.5 2152.8 1786.1 Paraspinal adipose tissue (cc) 149.1 140.9 471.1 135.4 Total abdominal adipose tissue (cc) 8112.0 10637.5 11938.4 8117.4 Limb Thigh muscle volume (cc) 3889.3 3713.5 2122.1 3971.2 Thigh SAT volume (cc) 1844.4 2416.1 2528.2 3651.8 Thigh IMAT volume (cc) 1100.7 1338.3 2414.9 1515.3 Calf muscle volume (cc) 1621.6 1358.8 971.5 1455.1 Calf SAT volume (cc) 283.8 767.6 333.9 712.3 Calf IMAT volume (cc) 100.6 706.5 397.7 211.0 IMCL (%) 1.29 0.90 4.08 1.50 EMCL (%) 3.89 6.03 21.99 3.32 IMCL: EMCL ratio 0.33 0.15 0.19 0.33 PDFF Liver (%) 15.73 13.45 Not available* 26.84 Pancreas (%) 7.21 7.25 Not available* 1.30 Thigh muscle (%) 5.05 6.29 28.35 3.92 Calf muscle (%) 6.50 11.25 27.60 9.07 *Liver and pancreas PDFF were not available due to motion artefacts. Discussion This report illustrates the variation of clinical presentation of non-acquired partial lipodystrophy in ethnic Chinese men, particularly adult males with the “typical” android pattern of fat distribution, and the utility of DXA and MRI for elucidating characteristics of partial lipodystrophy which was hitherto unsuspected. The strength of this study was that we were able to compare our cases to a slightly older man of the same ethnic group, with higher BMI but normal fat and muscle distribution in the lower limbs. Our three cases had relatively greater truncal and visceral adiposity, higher A/G ratio (a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome [ 1 , 2 ] associated with paucity of subcutaneous and limb fat as demonstrated by DXA and MRI, with correspondingly worse cardiometabolic outcomes compared to the control. Individuals with lipodystrophy may have total body fat within the “normal” range and a deceptively “less severe” degree of obesity based on BMI alone, but the accumulation of visceral lipids disrupt organ function and insulin action, particularly in the liver, heart and pancreas [ 10 , 11 , 17 – 22 ]. The severity of metabolic derangement in lipodystrophy is proportionate to the extent of fat and muscle loss and dysfunction [ 4 , 9 , 10 ]; in particular, intramyocellular lipid accumulation is associated with decreased mitochondrial fatty acid oxidative capacity [ 17 , 18 ] which may lead to dilated cardiomyopathy and conduction system abnormalities [ 19 – 21 ] (such as were present in Case 3 , who had severe wasting of both muscle and fat), highlighting the importance of screening and timely intervention for cardiac and metabolic abnormalities. Our three cases were diagnosed with lipodystrophy at least 10 years after the onset of diabetes (Cases 1 and 2 ) or several years after noticeable progressive wasting of limbs despite central obesity (Case 3 ). This accords with the significant delay in diagnosis of partial lipodystrophy worldwide [ 3 – 7 ], with an average of 10–24 years between onset of symptoms and diagnosis. Familial partial lipodystrophy type 1 (FPLD1, Kobberling variety) is characterized by central obesity which is especially marked in contrast to limb wasting due to fat loss [ 2 , 22 ]. Early recognition requires a high index of suspicion in the presence of increasing abdominal girth and relative wasting of subcutaneous fat in the limbs with negative investigations for Cushing syndrome, especially with multiple metabolic comorbidities at a young age and/or positive family history. However, accuracy and reliability of measurements are reduced as the skinfold thickness increases in individuals with severe obesity [ 23 ] and skinfold measurements underestimate the actual body fat percentage [ 24 ]. DXA images that highlighted an individual’s 2-dimensional fat distribution (“fat shadow”) allowed trained readers to distinguish patients with lipodystrophy from control individuals with 85% sensitivity and 96% specificity [ 25 ]. As fat distribution is a highly heritable trait and common genetic variation contributes to extreme fat genotypes including partial lipodystrophy [ 26 ], the use of MRI can enhance characterization of depot-specific visceral versus subcutaneous and gluteo-femoral adipose tissue with higher risk of insulin resistance, inflammation and cardiovascular disease in the former. Genetic testing in our cases was negative, but the genetic inheritance of FPLD1 has yet to be identified [ 2 ] especially in Asian populations in whom there is a paucity of data; our cases likely had polygenic forms of partial lipodystrophy. In contrast to women, in whom the expression and severity of partial lipodystrophy phenotypes are more evident and present at an earlier age [ 2 , 6 , 8 ], the difficulty in clinical diagnosis of lipodystrophy in men is compounded by the lack of distinct validated cut-offs and reproducibility of skinfold thickness measurements. Indeed, the sex distribution of partial lipodystrophy might be expected to be similar in view of autosomal or polygenic inheritance, but men comprised only 25% of a multinational cohort (USA, Turkey, Brazil) [ 4 ], 18% of a Spanish cohort [ 6 ] and 28% in a French national reference centre [ 7 ]. While ratios such as the KöB index (subscapular/calf skinfold ratio) perform well for diagnosis of FPLD1 in women (sensitivity 89% and specificity 84% at a threshold of 3.477 [ 22 ]), the KöB index has not been validated in men. In the UK Biobank comprising mostly adults of European ancestry), the fat mass ratio (FMR), defined as trunk fat percentage (trunk fat %) divided by leg fat percentage (leg fat %), demonstrated high sensitivity (88.9%) and specificity (93.8%) for discriminating women with FPLD from matched control subjects, with the 87th percentile of the female FMR distribution (corresponding to 1.2) [ 27 , 28 ] proposed as the cut-off for diagnosis of FPLD based on increased risk of type 2 diabetes, coronary artery disease, hypertension and metabolic-associated steatotic liver disease; this FMR corresponded to the 95th percentile in the Fenland study [ 29 ] which was a study of factors relating to obesity and diabetes in the UK. A recent analysis [ 30 ] which used the same percentiles of FMR in men (corresponding to 1.7) found that ∼1 in 8 participants of the UK Biobank and ∼1 in 20 participants of the Fenland cohort had elevated FMRs, ∼1,000 times more common than the reported clinical or genetic prevalence for FPLD [ 3 , 5 ]. The FMRs of Cases 2 and 3 were 1.30 and 1.20 (around the 50th percentile of 1.28 for Singaporean males aged 50) and Case 1 ’s FMR of 1.70 was just above the 90th percentile of 1.62 [ 16 ], illustrating that while FMR is useful to identify partial lipodystrophy, it is not conclusive per se and varies between different ethnic groups. The association of FMRs which are lower than the UK cut-offs with metabolic syndrome in our cases may be related to the higher cardiometabolic risk at lesser degrees of adiposity for Asian compared to Caucasian populations [ 12 ]. While the combination of clinical and imaging anthropometric measurements such as thigh skinfold and leg fat percentage have shown promise for diagnosis of FPLD1 in women in Brazil [ 31 ], more studies are needed to evaluate similar criteria and define cut-offs for FPLD diagnosis in men and in different ethnic groups. Our study is limited not only by the small number of men, but also that they were all ethnic Chinese from a single-centre in a small country in Southeast Asia, which underscores the challenges in differentiation of partial lipodystrophy from central obesity of a typically android distribution compounded by the relatively low awareness of the features of lipodystrophy among healthcare providers and the lack of clinical criteria even when the diagnosis is suspected, leading to under-diagnosis. As such, DXA and MRI are useful adjuncts to overcoming the limitations of clinical evaluation of suspected partial lipodystrophy. Conclusions This case series illustrates the variability in presentation and challenges of diagnosis of partial lipodystrophy in men, and highlights the clinical utility of DXA and MRI in the evaluation of lipodystrophy due to the difficulties of diagnosis of fat versus muscle wasting through visual inspection. While this distinctive pattern of central obesity with relatively slim limbs is noticeable in children, adolescents and young women, it may be difficult to differentiate from android fat distribution in older men. Milder forms of partial lipodystrophy may go unrecognized as well, and it has been suggested that these underlie the pathogenesis of type 2 diabetes in a higher proportion of the population than is reported [ 4 – 7 ]. Further large studies will be useful to quantify adipose tissue distribution and fat imaging phenotypes on DXA and MRI which can be used to define criteria for diagnosis of partial lipodystrophy in Asian populations, in whom the prevalence of obesity and type 2 diabetes is increasing. Patient Perspectives Our patients had never heard of lipodystrophy prior to evaluation. Having been advised that partial lipodystrophy is an inherited condition (even if not all the genes have been identified, especially in Asian populations) and increases the risk and severity of metabolic complications, Case 1 (family members with similar features of abdominal obesity and thin limbs) and Case 2 (strong family history of diabetes) were motivated to improve adherence to treatment for diabetes, and to increase awareness in possibly affected family members. When Case 3 was advised that his incongruously thin limbs in comparison to his progressively increasing abdominal girth were not only due to “lack of exercise” as he had thought, he was amenable to the use of anti-obesity medication which induced significant weight loss and reduction in abdominal adiposity. Declarations Clinical Trial Number : not applicable Consent to Publish declaration : Written informed consent for participation and publication was obtained for all patients of their personal or clinical details along with any identifying images Author Contributions : J.K., S.A.S., Y.J., S.S.V and W.J. L. conceptualized the study, formulated the methodology, performed the investigations and analyzed the data. J.K. and W.J.L prepared the original draft, and all authors were involved in review and editing, and approval of the manuscript for submission. J.K. and W.J.L. were responsible for obtaining funding. All authors have read and agreed to the published version of the manuscript. Funding : This study was an investigator-initiated study supported by the Changi General Hospital research fund. Ethics declaration : The study was conducted in accordance with the Declaration of Helsinki and approved by the SingHealth Institutional Review Board (protocol code 2015-2310 and date of approval 28th April 2015). Data Availability Statement : The data that support the findings of this study are available on request from the corresponding author. Competing Interests Declaration : The authors declare that they have no competing interests References Handelsman Y, Oral EA, Bloomgarden ZT, Brown RJ, Chan JL, Einhorn D, Garber AJ, Garg A, Garvey WT, Grunberger G, Henry RR, Lavin N, Tapiador CD, Weyer C; American Association of Clinical Endocrinologists. The clinical approach to the detection of lipodystrophy - an AACE consensus statement. Endocr Pract. 2013; 19(1):107-16. doi:10.4158/endp.19.1v767575m65p5mr06 Brown RJ, Araujo-Vilar D, Cheung PT, Dunger D, Garg A, Jack M, Mungai L, Oral EA, Patni N, Rother KI, von Schnurbein J, Sorkina E, Stanley T, Vigouroux C, Wabitsch M, Williams R, Yorifuji T. The diagnosis and management of lipodystrophy syndromes: a multi-society practice guideline. J Clin Endocrinol Metab. 2016; 101 (12):4500-11. doi: 10.1210/jc.2016-2466 Chiquette E, Oral EA, Garg A, Araújo-Vilar D, Dhankhar P. Estimating the prevalence of generalized and partial lipodystrophy: findings and challenges. Diabetes Metab Syndr Obes. 2017; 10:375-383. doi: 10.2147/DMSO.S130810 eCollection 2017. Akinci B, Oral EA, Neidert A, Rus D, Cheng WY, Thompson-Leduc P, Cheung HC, Bradt P, Foss de Freitas MC, Montenegro RM, Fernandes VO, Cochran E, Brown RJ. Comorbidities and survival in patients with lipodystrophy: an international chart review study. J Clin Endocrinol Metab. 2019;104(11): 5120-35. doi: 10.1210/jc.2018-02730 Gonzaga-Jauregui C, Ge W, Staples J, Van Hout C, Yadav A, Colonie R, Leader JB, Kirchner HL, Murray MF, Reid JG, Carey DJ, Overton JD, Shuldiner AR, Gottesman O, Gao S, Gromada J, Baras A, Altarejos J; Geisinger-Regeneron DiscovEHR collaboration. Clinical and Molecular Prevalence of Lipodystrophy in an Unascertained Large Clinical Care Cohort. Diabetes. 2020; 69(2):249-258. doi: 10.2337/db19-0447 Fernández-Pombo A, Sánchez-Iglesias S, Castro-Pais AI, Ginzo-Villamayor MJ, Cobelo-Gómez S, Prado-Moraña T, et al. Natural history and comorbidities of generalised and partial lipodystrophy syndromes in Spain. Front Endocrinol. (Lausanne) 2023; 14:1250203. doi: 10.3389/fendo.2023.1250203 Donadille B, Janmaat S, Mosbah H, Belalem I, Lamothe S, Nedelcu M, Jannot AS, Christin-Maitre S, Fève B, Vatier C, Vigouroux C. Diagnostic and referral pathways in patients with rare lipodystrophy and insulin-resistance syndromes: key milestones assessed from a national reference center. Orphanet J Rare Dis. 2024; 19(1):177. doi: 10.1186/s13023-024-03173-2. Loh WJ, Yaligar J, Hooper AJ, Sadananthan SA, Kway Y, Lim SC, Watts GF, Velan SS, Leow MKS, Khoo J. Clinical and imaging features of women with polygenic partial lipodystrophy: a case series. Nutr. Diabetes. 2024; 14,3 https://doi.org/10.1038/s41387-024-00260-y Mann JP, Savage DB. What lipodystrophies teach us about the metabolic syndrome. J Clin Invest. 2019; 129(10):4009-21. doi: 10.1172/JCI129190 Lim K, Haider A, Adams C, Sleigh A, Savage DB. Lipodistrophy: a paradigm for understanding the consequences of "overloading" adipose tissue. Physiol Rev. 2021; 101(3):907-93. doi: 10.1152/physrev.00032.2020 Loh WJ, Johnston DG, Oliver N, Godsland IF. Skinfold thickness measurements and mortality in white males during 27.7 years of follow-up. Int J Obes (Lond). 2018; 42(11):1939-45. doi:10.1038/s41366-018-0034-0 Nazare JA, Smith JD, Borel AL, Haffner SM, Balkau B, Ross R, Massien C, Alméras N, Després JP.. Ethnic influences on the relations between abdominal subcutaneous and visceral adiposity, liver fat, and cardiometabolic risk profile: the International Study of Prediction of Intra-Abdominal Adiposity and Its Relationship with Cardiometabolic Risk/Intra-Abdominal Adiposity. Am J Clin Nutr. 2012; 96(4): 714-26. doi: 10.3945/ajcn.112.035758 Marfell-Jones MJ, Stewart AD, De Ridder JH. International standards for anthropometric assessment. Wellington, New Zealand: International Society for the Advancement of Kinanthropometry 2012 Kway YM, Thirumurugan K, Michael N, Tan KH, Godfrey KM, Gluckman P, Chong YS, Venkataraman K, Khoo EYH, Khoo CM, Leow MK, Tai ES, Chan JK, Chan SY, Eriksson JG, Fortier MV, Lee YS, Velan SS, Feng M, Sadananthan SA. A fully convolutional neural network for comprehensive compartmentalization of abdominal adipose tissue compartments in MRI. Comput Biol Med. 2023; 167:107608. doi: 10.1016/j.compbiomed.2023.107608. Krssak M, Lindeboom L, Schrauwen-Hinderling V, Szczepaniak LS, Derave W, Lundborn J, et al., Proton magnetic resonance spectroscopy in skeletal muscle: Experts' consensus recommendations. NMR Biomed. 2021; 34(5): p. e4266. doi: 10.1002/nbm.4266 Soh BP, Lee SY, Wong WY, Pang BWJ, Lau LK, Jabbar KA, Seah WT, Chen KK, Srinivasan S, Ng TP, Wee SL. Body composition reference values in Singaporean adults using dual-energy X-ray absorptiometry-The Yishun study. PLoS One. 2022; 17(10):e0276434. doi: 10.1371/journal.pone.0276434 Gueugneau M, Coudy-Gandilhon C, Théron L, Meunier B, Barboiron C, Combaret L, Taillandier D, Polge C, Attaix D, Picard B, Verney J, Roche F, Féasson L, Barthélémy JC, Béchet D. Skeletal muscle lipid content and oxidative activity in relation to muscle fiber type in aging and metabolic syndrome. J Gerotol Ser A Biomed Sci Med Sci. 2015; 70 (5): 566-76. doi: 10.1093/gerona/glu086 Simha V, Lanza IR, Dasari S, Klaus KA, Le Brasseur N, Vuckovic I, Laurenti MC, Cobelli C, Port JD, Nair KS. Impaired muscle mitochondrial function in familial partial lipodystrophy. J Clin Endocrinol Metab. 2022; 107(2):346-62. doi: 10.1210/clinem/dgab725 Eldin AJ, Akinci B, da Rocha AM, Meral R, Simsir IY, Adiyaman SC, Ozpelit E, Bhave N, Gen R, Yurekli B, Ozdemir Kutbay N, Siklar Z, Neidert AH, Hench R, Tayeh MK, Innis JW, Jalife J, Oral H, Oral EA. Cardiac phenotype in familial partial lipodystrophy. Clin Endocrinol. 2021; 94:1043–1053. doi: 10.1111/cen.14426 Ajluni N, Meral R, Neidert AH, Brady GF, Buras E, McKenna B, DiPaola F, Chenevert TL, Horowitz JF, Buggs-Saxton C, Rupani AR, Thomas PE, Tayeh MK, Innis JW, Omary MB, Conjeevaram H, Oral EA. Spectrum of disease associated with partial lipodystrophy: lessons from a trial cohort. Clin Endocrinol (Oxf). 2017; 86(5): 698-707. doi: 10.1111/cen.13311. Hussain I, Patni N, Garg A. Lipodystrophies, dyslipidaemias and atherosclerotic cardiovascular disease. Pathology. 2019; 51(2):202-12. doi: 10.1016/j.pathol.2018.11.004 Guillín-Amarelle C, Sánchez-Iglesias S, Castro-Pais A, Rodriguez-Cañete L, Ordóñez-Mayán L, Pazos M, González-Méndez B, Rodríguez-García S, Casanueva FF, Fernández-Marmiesse A, Araújo-Vilar D. Type 1 familial partial lipodystrophy: understanding the Kobberling syndrome. Endocrine. 2016; 54(2): 411-21. doi: 10.1007/s12020-016-1002-x. Friedl KE, Westphal KA, Marchitelli LJ., Patton JF, Chumlea WC, Guo SS. Evaluation of anthropometric equations to assess body-composition changes in young women. Am J Clin Nutr. 2001; 73: 268–75. doi: 10.1093/ajcn/73.2.268. Erratum in: Am J Clin Nutr. 2002; 76(3):695 Pineau JC, Frey A. Comparison of skinfold thickness models with DEXA: impact of visceral adipose tissue. J Sports Med Phys Fitness. 2016; 56(5):541–5. Meral R, Ryan BJ, Malandrino N, Jalal A, Neidert AH, Muniyappa R, Akıncı B, Horowitz JF, Brown RJ, Oral EA. "Fat shadows" from DXA for the qualitative assessment of lipodystrophy: when a picture is worth a thousand numbers. Diabetes Care. 2018; 41(10):2255-2258. doi: 10.2337/dc18-0978 Agrawal S, Wang M, Klarqvist MDR, Smith K, Shin J, Dashti H, Diamant N, Choi SH, Jurgens SJ, Ellinor PT, Philippakis A, Claussnitzer M, Ng K, Udler MS, Batra P, Khera AV. Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots. Nat Commun. 2022; 13(1):3771. doi: 10.1038/s41467-022-30931-2. Valerio CM, Zajdenverg L, de Oliveira JE, Mory PB, Moises RS, Godoy-Matos AF. Body composition study by dual-energy x-ray absorptiometry in familial partial lipodystrophy: finding new tools for an objective evaluation. Diabetol Metab Syndr. 2012; 4(1):40. doi: 10.1186/1758-5996-4-40 Vasandani C, Li X, Sekizkardes H, Adams-Huet B, Brown RJ, Garg A. Diagnostic value of anthropometric measurements for familial partial lipodystrophy, Dunnigan variety. J Clin Endocrinol Metab. 2020; 105(7): 2132-41. doi: 10.1210/clinem/dgaa137 O'Connor L, Brage S, Griffin SJ, Wareham NJ, Forouhi NG. The cross-sectional association between snacking behaviour and measures of adiposity: the Fenland Study, UK. Br J Nutr. 2015; 114(8):1286-93. doi: 10.1017/S000711451500269X. Agrawal S, Luan J, Cummings BB, Weiss EJ, Wareham NJ, Khera AV. Relationship of fat mass ratio, a biomarker for lipodystrophy, with cardiometabolic traits. Diabetes. 2024; 73(7):1099-1111. doi: 10.2337/db23-0575. Veras VR, da Cruz Paiva Lima GE, da Ponte Melo I, Fernandes VO, de Moura Lopes FK, do Amaral CL, Castelo MHG, Queiroz LL, Araújo JS, Valerio CM, Montenegro Junior RM. Anthropometric measurements as a key diagnostic tool for familial partial lipodystrophy in women. Diabetol Metab Syndr. 2024; 16(1):216. doi: 10.1186/s13098-024-01413-w. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 03 Jul, 2025 Editor assigned by journal 02 Jul, 2025 Editor invited by journal 12 Jun, 2025 Submission checks completed at journal 11 Jun, 2025 First submitted to journal 11 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6756323","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":481124578,"identity":"24d354e1-e358-4b1a-8397-9e9a5b3a3426","order_by":0,"name":"Joan Khoo","email":"data:image/png;base64,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","orcid":"","institution":"Changi General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Joan","middleName":"","lastName":"Khoo","suffix":""},{"id":481124579,"identity":"bd22bdf9-84e0-4c27-adb4-e24542aafea1","order_by":1,"name":"Suresh Anand Sadananthan","email":"","orcid":"","institution":"Singapore Institute for Clinical Sciences, Agency for Science Technology and Research","correspondingAuthor":false,"prefix":"","firstName":"Suresh","middleName":"Anand","lastName":"Sadananthan","suffix":""},{"id":481124580,"identity":"e046974e-2671-4027-b2bf-98bef08650f7","order_by":2,"name":"Jadegoud Yaligar","email":"","orcid":"","institution":"Singapore Institute for Clinical Sciences, Agency for Science Technology and Research","correspondingAuthor":false,"prefix":"","firstName":"Jadegoud","middleName":"","lastName":"Yaligar","suffix":""},{"id":481124581,"identity":"4407016a-9aa2-4638-9229-5fa155cd1e68","order_by":3,"name":"Sambasivam Sendhil Velan","email":"","orcid":"","institution":"Singapore Institute for Clinical Sciences, Agency for Science Technology and Research","correspondingAuthor":false,"prefix":"","firstName":"Sambasivam","middleName":"Sendhil","lastName":"Velan","suffix":""},{"id":481124582,"identity":"6637cb6e-9adf-4fc6-ba66-0a48401133cc","order_by":4,"name":"Wann Jia Loh","email":"","orcid":"","institution":"Changi General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wann","middleName":"Jia","lastName":"Loh","suffix":""}],"badges":[],"createdAt":"2025-05-27 07:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6756323/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6756323/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86218329,"identity":"c71931de-2c7f-4dea-af6b-ec4c3778602f","added_by":"auto","created_at":"2025-07-08 06:26:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":721194,"visible":true,"origin":"","legend":"\u003cp\u003eDXA and MRI features in 3 Chinese men (Cases 1, 2 and 3) with metabolic syndrome and clinical features suggesting appearance of partial lipodystrophy of the limbs, for comparison with an abdominally obese control of similar ethnicity and BMI. MRI images shown in colour: abdominal deep subcutaneous adipose tissue (green), superficial subcutaneous adipose tissue (red), intraperitoneal adipose tissue (blue), retroperitoneal adipose tissue (yellow), and paraspinal adipose tissue (cyan). The three cases have higher fat % trunk to fat % leg ratios and trunk/leg fat mass ratios compared with Control, indicating subcutaneous fat wasting in the legs, in contrast to adipose accumulation in the abdomen. Case 3 had, in addition, marked muscle wasting even compared to Cases 1 and 2.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6756323/v1/cc1890b911408da6bff7e4dd.png"},{"id":86219428,"identity":"644a2e87-367d-4ec6-960f-8e1b7065478a","added_by":"auto","created_at":"2025-07-08 06:42:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1517833,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6756323/v1/52aebf5e-1e81-4526-82cd-133c3a371639.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The utility of DXA and MRI for overcoming the limitations of clinical evaluation in diagnosis of partial lipodystrophy in Chinese men with metabolic syndrome: a case series","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLipodystrophies are a heterogeneous group of congenital and acquired disorders with either partial or generalized loss of into subcutaneous adipose tissue (SAT) [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This atypical distribution of adiposity and reduced capacity of subcutaneous lipid storage leads to insulin resistance, inflammation, dysregulation in adipokine secretion and ectopic fat accumulation, resulting in type 2 diabetes (T2DM), fatty liver disease and other metabolic comorbidities, leading to significant morbidity and premature mortality [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9 CR10\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In partial forms, fat loss affects particularly the lower limbs and instead adipose tissue may accumulate in the abdomen, face and neck. There is currently no clear consensus on clinical or imaging criteria for diagnosis of partial lipodystrophy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Moreover, individuals of different ethnicity with similar BMI have different metabolic profiles due to variation in degree of abdominal (visceral) adiposity and muscle mass: in particular, East Asian (Chinese, Japanese, Korean) adults have a higher percentage of visceral fat and a more deleterious cardiometabolic risk profile compared to white Europeans, despite having a lower BMI [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While the reported prevalence of lipodystrophy ranges from 1.3\u0026ndash;4.7 per million based on electronic medical record databases in the UK and USA and the prevalence of lipodystrophy is about 2.63 per million in Europe [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], there ais a paucity of data in Asian populations in whom lipodystrophy is likely under-recognized [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although partial lipodystrophies appear to be more detrimental to women compared to men [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], males with partial lipodystrophy syndromes are also at increased risk of metabolic complications.\u003c/p\u003e \u003cp\u003eIn this report, we describe clinical features, metabolic profile and cardiovascular outcomes in men of East Asian (Chinese) descent with metabolic syndrome and similar BMI in the overweight/obese range, three of whom (cases) had features suggestive of partial lipodystrophy of the legs. Skinfold thickness measurements and body composition analysis using DXA and MRI scan were used to compare the cases with a control of the same ethnic group with similar age and BMI who also presented with metabolic syndrome and self-reported leg wasting, with the aim of elucidating differences in visceral and subcutaneous fat distribution to aid in the diagnosis of partial lipodystrophy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe studied three cases of Chinese men with similar BMI of 28-30 kg/m\u003csup\u003e2\u003c/sup\u003e with features suggesting partial lipodystrophy, who were managed in the endocrinology clinic of Changi General Hospital in Singapore, a Southeast Asian country with a predominantly ethnic Chinese population. For comparison, we recruited a fourth Chinese man as a \u0026lsquo;control\u0026rsquo; with normal android body fat distribution and recent weight gain. The cases were initially suspected to have partial lipodystrophy based on the presence of preferential and symmetrical fat loss of the legs, with normal or increased distribution of fat on the face, neck and trunk. All patients underwent extensive history taking, physical examination and investigations to exclude endogenous and exogenous Cushing\u0026rsquo;s syndrome, human immunodeficiency virus infection, anti-retroviral therapy and cancer. This study was approved by the SingHealth Institutional Review Board ((protocol code 2015-2310 and date of approval 28th April 2015). All study participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSkinfold measurement and bioelectrical impedance analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 7-site skinfold measurement using Harpenden calipers were performed at these body sites: triceps, biceps, subscapular, suprailiac (otherwise known as supraspinale), abdomen, thigh, and calf of the right side of the body, as described in the international standards for anthropometric assessment, recommended by the International Society for the Advancement of Kinanthropometry [13]. To minimise inter-observer variability, skinfold readings at each of the seven sites were done by one trained personnel and averaged. Bioelectrical impedance analysis (BIA) was performed with the Tanita body composition analyser.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratory and genetic testing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFasting venous blood samples were taken for measurement of serum total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol concentrations (LDL-C), glucose and insulin as previously described [8]. The homeostasis model assessment index of insulin resistance (HOMA-IR) was calculated from glucose (mmol/L) x insulin (mU/L)/22.5. In Cases 2 and 3, extensive genetic testing was performed using whole genome sequencing for monogenic causes of FPLD, obesity, diabetes, severe hypertriglyceridemia, and severe insulin resistance as previously described [8]. In Case 1, the genetic panel was tested using massively parallel targeted-gene sequencing for 16 MODY- and lipodystrophy-associated genes that included PPARy and LMNA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDual-energy X-ray absorptiometry (DXA) and MRI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDXA scans were performed using Hologic QDR 4500A, fan-beam densitometer (Hologic, Inc., Bedford, Massachusetts, software version 8.21) to measure whole body composition, as previously described [8]. Including fat of total body, head, trunk, arms and legs, abdominal visceral adipose tissue (VAT), android and gynoid fat masses, and trunk to leg % fat ratio (FMR). Android and gynoid (A/G) regions were defined by the Hologic APEX software used in the scan analysis. The A/G ratio is a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome [14]. g term precision QC monitoring on phantoms for three years on the Hologic densitometer was 0.01%. Whole body MRI was performed using Siemens Prisma 3T MR scanner, except for Case 3 with implantable cardioverter defibrillator who used Siemens Sola 1.5T MR scanner. Dixon fat-water imaging sequences were used in abdominal MRI to quantify deep subcutaneous adipose tissue (DSAT), superficial subcutaneous adipose tissue (SSAT), intraperitoneal adipose tissue (IPAT), retroperitoneal adipose tissue (RPAT), and paraspinal adipose tissue (PSAT) between L1 and L5 vertebrae [14]. The mean proton density fat fraction (PDFF) were determined from the multi-echo Dixon fat-water imaging sequence and quantified as from ROIs selected within liver, pancreas, and thigh and calf muscles [8]. The intramyocellular (IMCL) and extramyocellular (EMCL) lipids within the soleus muscle were determined using magnetic resonance spectroscopy (MRS) [15]. The IMCL and EMCLwere expressed as a ratio with respect to water.\u0026nbsp;\u003c/p\u003e"},{"header":"Case presentations","content":"\u003cp\u003e\u003cstrong\u003eCase 1\u003c/strong\u003e \u0026ndash; Partial lipodystrophy features and poorly controlled diabetes\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHe was diagnosed with type 2 diabetes at age 40 when he presented with osmotic symptoms. His diabetes was initially well-controlled (HbA1c 7%) with increasing doses of oral glucose-lowering medications (OGLD) but gradually worsening glycaemic control requiring addition of insulin glargine at age 45. His HbA1c ranged from 10-12% for the next 5 years, despite steadily increasing insulin doses, leading to referral at age 50 to an endocrinologist who observed that he had acanthosis nigricans, abdominal adiposity, and relatively thin thighs. The limb wasting was atypical for diabetic amyotrophy, being painless and not associated with muscular weakness. There was a history of diabetes on the paternal side of the family and he suspected that some male and female paternal cousins had similar limb wasting with truncal obesity, though this was difficult to confirm as they were not on follow-up in our institution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHis weight was 84.5 kg (BMI 28.2 kg/m\u003csup\u003e2\u003c/sup\u003e), and anthropometric measurements revealed very low thigh skinfold thickness at 8.5 mm (Table 1), with subcutaneous fat loss and preserved muscle mass in his limbs confirmed on DXA and MRI scans (Figure 1). In contrast, he had a relatively high volume of truncal fat with A/G ratio 1.61, VAT/SAT ratio 1.42, trunk: leg fat ratio 2.07 (99th percentile for sex and age compared to men in Singapore [16]) and high ratio of trunk fat percentage to leg fat percentage (fat mass ratio, FMR) of 1.70 (above 90th percentile [16]) as well as high liver and pancreas PDFF (Table 1) on MRI, indicating significant greater visceral adiposity as a proportion of total body fat. Genetic testing was negative for monogenic diabetes of young onset (MODY) and the major lipodystrophy genes PPARY and LMNA. \u0026nbsp;He was informed of the likely diagnosis of partial lipodystrophy and increased risk of metabolic complications. This diagnosis motivated him to adhere to diet, exercise and medications, with subsequent improvement of HbA1c to 7.9%. He was counselled to advise his cousins to consult their physicians regarding evaluation for lipodystrophy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCase 2\u003c/strong\u003e\u0026ndash;- Partial lipodystrophy features and long-standing diabetes with microvascular and macrovascular complications\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHe was diagnosed with diabetes at the age of 35, with a strong family history of type 2 diabetes (both parents, two siblings, maternal grandparents and cousins). Over the decade following his diagnosis, his glycaemic control progressively worsened, complicated by diabetic nephropathy, proliferative retinopathy, peripheral vascular disease and gangrene necessitating amputation of three toes on his right foot. During admission at age 50 for osteomyelitis of his right foot, he was noted during endocrinology review (for optimization of glycaemic control) to have relatively slim lower limbs in comparison to central obesity (waist circumference of 110 cm, weight 95 kg, BMI 30.6 kg/m\u003csup\u003e2\u003c/sup\u003e), and acanthosis nigricans in the axillary region. On examination, there was paucity of subcutaneous fat, with a thigh skinfold thickness 19.2 mm and calf skinfold thickness 18.9 mm (Table 1). This relatively large volume of visceral trunk compared to subcutaneous (limb) adipose tissue was confirmed on DXA bioimpedance analysis by a very high trunk to leg fat ratio of 1.53 (99th percentile for sex and age) [16], A/G ratio 1.43 and FMR 1.30 (above 50th percentile [16]) (Figure 1). His MRI also demonstrated very high visceral fat content with relatively low thigh and calf SAT volumes with VAT/SAT ratio 1.88, and elevated liver and pancreas PDFF.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite being adherent to high doses of premix insulin, his glycaemic control was poor, with HbA1c ranging from 8.4-10%, and he was changed to a basal-bolus regime with improvement in HbA1c. He was not keen for prescription of liraglutide due to the cost. While genetic testing was negative for all monogenic mutations of familial lipodystrophy syndromes, obesity, severe insulin resistance and MODY, he was advised of the clinical diagnosis of partial lipodystrophy, and to ask his family members with diabetes if they had noticed increasing abdominal girth or limb wasting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCase 3\u003c/strong\u003e \u0026ndash; Severe wasting of lower limb adiposity and muscles with increased abdominal adiposity and cardiomyopathy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHe was hospitalised for newly-diagnosed heart failure at age 50 and found to have dilated cardiomyopathy (left ventricular ejection fraction 35%) with normal coronary arteries on angiogram. He had never smoked nor drunk alcohol and did not have diabetes, but was found to have dyslipidaemia and hypertension. There was no family history of diabetes. He had been steadily gaining weight in the last 10 year despite efforts at diet and exercise, with maximum weight at the time of admission. Physical examination revealed acanthosis nigricans and significant abdominal obesity (weight 94.2 kg, BMI 30.5 kg/m\u003csup\u003e2\u003c/sup\u003e, waist circumference 122 cm), which did not decrease significantly after weight loss with diuresis. Despite his weight, he had incongruously little fat in his legs, particularly in the lower leg (reduced calf skinfold thickness 11.9 mm, the lowest of all 3 cases), raising the suspicion of partial lipodystrophy.\u003c/p\u003e\n\u003cp\u003eHis K\u0026ouml;B index (subscapular/calf skinfold ratio, a measure of relative subcutaneous fat in upper:lower limbs) of 2.69 was the highest of the 3 patients (Table 1), consistent with more severe wasting of subcutaneous fat in the legs. He had the lowest limb lean mass (thigh and calf muscle) volume of the 3 cases (Table 1), with MRI confirmation of the presence of severe muscle loss in addition to subcutaneous adipose tissue wasting in his legs (Table 1, Figure 1). In particular, he had fatty infiltration of thigh and calf muscles, as evidenced by high PDFF and intra- and extra-myocellular lipid accumulation on MRI (Figure 1). History and investigations were negative for endogenous or exogenous Cushing\u0026rsquo;s syndrome. Genetic testing was negative for monogenic mutations of familial lipodystrophy, obesity, severe insulin resistance and MODY. He was advised of the clinical diagnosis of partial lipodystrophy and agreed to start liraglutide, after which his weight decreased to 85 kg (11.1% reduction from baseline) and waist circumference decreased by 7 cm, though exercise was limited by cardiac dysfunction. He eventually required an implantable cardioverter defibrillator due to recurrent ventricular tachycardia which was unresponsive to medical therapy and led to sudden cardiac death at age 54.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e \u0026ndash; android pattern of central obesity, muscle mass and metabolic profile improved with lifestyle changes\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHe was a 56-year-old man at the time of referral to the endocrinology clinic, whose weight had increased from 80 kg to 95 kg (BMI 31.7 kg/m\u003csup\u003e2\u003c/sup\u003e) over two years due to increased food intake from delivery platforms, and gym closures and lockdowns during the CoviD-19 pandemic. His waist circumference had also increased from 100cm to 109 cm, in association with self-reported reduction in his limb muscle bulk. However, in contrast to the 3 cases, his total body fat mass measured with BIA was lower, despite similar or higher thigh and calf skinfold thicknesses suggesting more lower limb subcutaneous fat. Despite higher BMI and age, his total body fat percentage was lower at 19.3% than the other three whose fat percentage ranged from 24.9 to 44.7% (Table 1), and his visceral and subcutaneous adipose tissue volumes within the expected range for men his age (T- and Z-scores 0.9 and 1.5 on DXA), in contrast to the 3 cases. Likewise, his A/G ratio 1.21 and VAT/SAT ratio 1.10 were within the normal ranges for Singapore men [16], and his trunk: leg fat ratio and FMR were lower than the cases (Table 1). With improved adherence to diet and increased exercise he lost 9 kg, reduced his waist circumference by 7 cm, and his blood pressure and serum triglycerides reduced to normal levels without the use of medications, as well as. increased arm and leg muscle mass.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: Anthropometry, metabolic features and body composition measured with skinfold calipers, bioimpedance and DXA, of four men with features of lipodystrophy. OGLD = oral glucose-lowering drugs. BIA = biolelectrical impedance analysis. Fat % trunk to fat % leg ratio = percentage of fat in trunk divided by percentage of fat in leg. The A/G ratio is a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome. FMR = fat mass ratio (ratio of trunk fat percentage to leg fat percentage).\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase 1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eChinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eChinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eChinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eChinese\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eHypertriglyceridaemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eDiabetes (age at diagnosis)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eYes (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eYes (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eDiabetes treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eOGLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eInsulin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eHOMA-IR at evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e9.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNot done\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAnthropometry\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e30.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e30.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e31.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eWaist circumference (cm)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eSubscapular skinfold (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e29.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eThigh skinfold (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e22.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e26.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eCalf skinfold (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e20.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eSubscapular to thigh skinfold ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eSuprailiac to thigh skinfold ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eK\u0026ouml;B index (subscapular/calf skinfold ratio)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eBody fat mass (kg) by BIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e21.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e27.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e42.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 652px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDXA\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eBody fat percentage (total)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e27.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e44.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e19.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eTotal lean mass/height\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e18.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e20.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eAbdominal VAT volume (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eAndroid to gynoid (A/G) ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eRight leg fat mass (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2737.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e4925.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4616.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e5249.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eRight leg lean mass (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e9248.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e9749.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7166.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9538.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eTrunk/leg fat mass ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e% fat trunk to % fat leg ratio (FMR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 2.\u003c/strong\u003e MRI features of adipose tissue distribution and muscle of four men with metabolic syndrome and features of lipodystrophy. SAT = subcutaneous adipose tissue. VAT = visceral adipose tissue. IMAT = intramuscular adipose tissue. PDFF: proton density fat fraction. IMCL=Intramyocellular lipids (%); EMCL=Extramyocellular lipids (%) expressed as a ratio with respect to water.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase 1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbdominal adiposity volume\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 425px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eAbdominal SAT (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3345.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3690.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e5404.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3860.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eAbdominal superficial SAT (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1706.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2180.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1991.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2098.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eAbdominal deep SAT (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1638.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1509.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3411.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1761.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eAbdominal VAT (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e4766.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e6944.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e6559.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4256.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eAbdominal VAT/SAT ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eIntraperitoneal adipose tissue (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3158.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3842.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3910.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2336.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eRetroperitoneal adipose tissue (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1459.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2964.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2152.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1786.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eParaspinal adipose tissue (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e149.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e140.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e471.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e135.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eTotal abdominal adipose tissue (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e8112.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e10637.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e11938.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e8117.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLimb\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThigh muscle volume (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3889.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3713.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2122.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3971.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThigh SAT volume (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1844.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2416.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2528.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3651.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThigh IMAT volume (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1100.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1338.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2414.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1515.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eCalf muscle volume (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1621.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1358.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e971.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1455.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eCalf SAT volume (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e283.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e767.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e333.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e712.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eCalf IMAT volume (cc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e100.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e706.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e397.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e211.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eIMCL (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e4.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eEMCL (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e6.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e21.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eIMCL: EMCL ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePDFF\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eLiver (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e15.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e13.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNot available*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e26.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003ePancreas (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e7.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e7.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNot available*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThigh muscle (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e5.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e28.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eCalf muscle (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e6.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e11.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e27.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Liver and pancreas PDFF were not available due to motion artefacts.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis report illustrates the variation of clinical presentation of non-acquired partial lipodystrophy in ethnic Chinese men, particularly adult males with the \u0026ldquo;typical\u0026rdquo; android pattern of fat distribution, and the utility of DXA and MRI for elucidating characteristics of partial lipodystrophy which was hitherto unsuspected. The strength of this study was that we were able to compare our cases to a slightly older man of the same ethnic group, with higher BMI but normal fat and muscle distribution in the lower limbs. Our three cases had relatively greater truncal and visceral adiposity, higher A/G ratio (a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] associated with paucity of subcutaneous and limb fat as demonstrated by DXA and MRI, with correspondingly worse cardiometabolic outcomes compared to the control. Individuals with lipodystrophy may have total body fat within the \u0026ldquo;normal\u0026rdquo; range and a deceptively \u0026ldquo;less severe\u0026rdquo; degree of obesity based on BMI alone, but the accumulation of visceral lipids disrupt organ function and insulin action, particularly in the liver, heart and pancreas [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The severity of metabolic derangement in lipodystrophy is proportionate to the extent of fat and muscle loss and dysfunction [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]; in particular, intramyocellular lipid accumulation is associated with decreased mitochondrial fatty acid oxidative capacity [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] which may lead to dilated cardiomyopathy and conduction system abnormalities [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] (such as were present in Case \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, who had severe wasting of both muscle and fat), highlighting the importance of screening and timely intervention for cardiac and metabolic abnormalities.\u003c/p\u003e \u003cp\u003eOur three cases were diagnosed with lipodystrophy at least 10 years after the onset of diabetes (Cases \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"FPar2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) or several years after noticeable progressive wasting of limbs despite central obesity (Case \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This accords with the significant delay in diagnosis of partial lipodystrophy worldwide [\u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], with an average of 10\u0026ndash;24 years between onset of symptoms and diagnosis. Familial partial lipodystrophy type 1 (FPLD1, Kobberling variety) is characterized by central obesity which is especially marked in contrast to limb wasting due to fat loss [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Early recognition requires a high index of suspicion in the presence of increasing abdominal girth and relative wasting of subcutaneous fat in the limbs with negative investigations for Cushing syndrome, especially with multiple metabolic comorbidities at a young age and/or positive family history. However, accuracy and reliability of measurements are reduced as the skinfold thickness increases in individuals with severe obesity [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and skinfold measurements underestimate the actual body fat percentage [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. DXA images that highlighted an individual\u0026rsquo;s 2-dimensional fat distribution (\u0026ldquo;fat shadow\u0026rdquo;) allowed trained readers to distinguish patients with lipodystrophy from control individuals with 85% sensitivity and 96% specificity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. As fat distribution is a highly heritable trait and common genetic variation contributes to extreme fat genotypes including partial lipodystrophy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], the use of MRI can enhance characterization of depot-specific visceral versus subcutaneous and gluteo-femoral adipose tissue with higher risk of insulin resistance, inflammation and cardiovascular disease in the former. Genetic testing in our cases was negative, but the genetic inheritance of FPLD1 has yet to be identified [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] especially in Asian populations in whom there is a paucity of data; our cases likely had polygenic forms of partial lipodystrophy.\u003c/p\u003e \u003cp\u003eIn contrast to women, in whom the expression and severity of partial lipodystrophy phenotypes are more evident and present at an earlier age [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], the difficulty in clinical diagnosis of lipodystrophy in men is compounded by the lack of distinct validated cut-offs and reproducibility of skinfold thickness measurements. Indeed, the sex distribution of partial lipodystrophy might be expected to be similar in view of autosomal or polygenic inheritance, but men comprised only 25% of a multinational cohort (USA, Turkey, Brazil) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], 18% of a Spanish cohort [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and 28% in a French national reference centre [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. While ratios such as the K\u0026ouml;B index (subscapular/calf skinfold ratio) perform well for diagnosis of FPLD1 in women (sensitivity 89% and specificity 84% at a threshold of 3.477 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]), the K\u0026ouml;B index has not been validated in men. In the UK Biobank comprising mostly adults of European ancestry), the fat mass ratio (FMR), defined as trunk fat percentage (trunk fat %) divided by leg fat percentage (leg fat %), demonstrated high sensitivity (88.9%) and specificity (93.8%) for discriminating women with FPLD from matched control subjects, with the 87th percentile of the female FMR distribution (corresponding to 1.2) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] proposed as the cut-off for diagnosis of FPLD based on increased risk of type 2 diabetes, coronary artery disease, hypertension and metabolic-associated steatotic liver disease; this FMR corresponded to the 95th percentile in the Fenland study [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] which was a study of factors relating to obesity and diabetes in the UK. A recent analysis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] which used the same percentiles of FMR in men (corresponding to 1.7) found that \u0026sim;1 in 8 participants of the UK Biobank and \u0026sim;1 in 20 participants of the Fenland cohort had elevated FMRs, \u0026sim;1,000 times more common than the reported clinical or genetic prevalence for FPLD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The FMRs of Cases \u003cspan refid=\"FPar2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e3\u003c/span\u003e were 1.30 and 1.20 (around the 50th percentile of 1.28 for Singaporean males aged 50) and Case \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026rsquo;s FMR of 1.70 was just above the 90th percentile of 1.62 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], illustrating that while FMR is useful to identify partial lipodystrophy, it is not conclusive \u003cem\u003eper se\u003c/em\u003e and varies between different ethnic groups. The association of FMRs which are lower than the UK cut-offs with metabolic syndrome in our cases may be related to the higher cardiometabolic risk at lesser degrees of adiposity for Asian compared to Caucasian populations [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While the combination of clinical and imaging anthropometric measurements such as thigh skinfold and leg fat percentage have shown promise for diagnosis of FPLD1 in women in Brazil [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], more studies are needed to evaluate similar criteria and define cut-offs for FPLD diagnosis in men and in different ethnic groups. Our study is limited not only by the small number of men, but also that they were all ethnic Chinese from a single-centre in a small country in Southeast Asia, which underscores the challenges in differentiation of partial lipodystrophy from central obesity of a typically android distribution compounded by the relatively low awareness of the features of lipodystrophy among healthcare providers and the lack of clinical criteria even when the diagnosis is suspected, leading to under-diagnosis. As such, DXA and MRI are useful adjuncts to overcoming the limitations of clinical evaluation of suspected partial lipodystrophy.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis case series illustrates the variability in presentation and challenges of diagnosis of partial lipodystrophy in men, and highlights the clinical utility of DXA and MRI in the evaluation of lipodystrophy due to the difficulties of diagnosis of fat versus muscle wasting through visual inspection. While this distinctive pattern of central obesity with relatively slim limbs is noticeable in children, adolescents and young women, it may be difficult to differentiate from android fat distribution in older men. Milder forms of partial lipodystrophy may go unrecognized as well, and it has been suggested that these underlie the pathogenesis of type 2 diabetes in a higher proportion of the population than is reported [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Further large studies will be useful to quantify adipose tissue distribution and fat imaging phenotypes on DXA and MRI which can be used to define criteria for diagnosis of partial lipodystrophy in Asian populations, in whom the prevalence of obesity and type 2 diabetes is increasing.\u003c/p\u003e\n\u003ch3\u003ePatient Perspectives\u003c/h3\u003e\n\u003cp\u003eOur patients had never heard of lipodystrophy prior to evaluation. Having been advised that partial lipodystrophy is an inherited condition (even if not all the genes have been identified, especially in Asian populations) and increases the risk and severity of metabolic complications, Case \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (family members with similar features of abdominal obesity and thin limbs) and Case \u003cspan refid=\"FPar2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (strong family history of diabetes) were motivated to improve adherence to treatment for diabetes, and to increase awareness in possibly affected family members. When Case \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e3\u003c/span\u003e was advised that his incongruously thin limbs in comparison to his progressively increasing abdominal girth were not only due to \u0026ldquo;lack of exercise\u0026rdquo; as he had thought, he was amenable to the use of anti-obesity medication which induced significant weight loss and reduction in abdominal adiposity.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e: not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration\u003c/strong\u003e: Written informed consent for participation and publication was obtained for all patients of their personal or clinical details along with any identifying images\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: J.K., S.A.S., Y.J., S.S.V and W.J. L. conceptualized the study, formulated the methodology, performed the investigations and analyzed the data. J.K. and W.J.L prepared the original draft, and all authors were involved in review and editing, and approval of the manuscript for submission. J.K. and W.J.L. were responsible for obtaining funding. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This study was an investigator-initiated study supported by the Changi General Hospital research fund.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e: The study was conducted in accordance with the Declaration of Helsinki and approved by the SingHealth Institutional Review Board (protocol code 2015-2310 and date of approval 28th April 2015).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e: The data that support the findings of this study are available on request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests Declaration\u003c/strong\u003e: The authors declare that they have no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHandelsman Y, Oral EA, Bloomgarden ZT, Brown RJ, Chan JL, Einhorn D, Garber AJ, Garg A, Garvey WT, Grunberger G, Henry RR, Lavin N, Tapiador CD, Weyer C; American Association of Clinical Endocrinologists. The clinical approach to the detection of lipodystrophy - an AACE consensus statement. Endocr Pract. 2013; 19(1):107-16. doi:10.4158/endp.19.1v767575m65p5mr06\u003c/li\u003e\n \u003cli\u003eBrown RJ, Araujo-Vilar D, Cheung PT, Dunger D, Garg A, Jack M, Mungai L, Oral EA, Patni N, Rother KI, von Schnurbein J, Sorkina E, Stanley T, Vigouroux C, Wabitsch M, Williams R, Yorifuji T. The diagnosis and management of lipodystrophy syndromes: a multi-society practice guideline. J Clin Endocrinol Metab. 2016; 101 (12):4500-11. doi: 10.1210/jc.2016-2466\u003c/li\u003e\n \u003cli\u003eChiquette E, Oral EA, Garg A, Ara\u0026uacute;jo-Vilar D, Dhankhar P. Estimating the prevalence of generalized and partial lipodystrophy: findings and challenges. Diabetes Metab Syndr Obes. 2017; 10:375-383. doi: 10.2147/DMSO.S130810 eCollection 2017.\u003c/li\u003e\n \u003cli\u003eAkinci B, Oral EA, Neidert A, Rus D, Cheng WY, Thompson-Leduc P, Cheung HC, Bradt P, Foss de Freitas MC, Montenegro RM, Fernandes VO, Cochran E, Brown RJ. Comorbidities and survival in patients with lipodystrophy: an international chart review study. J Clin Endocrinol Metab. 2019;104(11): 5120-35. doi: 10.1210/jc.2018-02730\u003c/li\u003e\n \u003cli\u003eGonzaga-Jauregui C, Ge W, Staples J, Van Hout C, Yadav A, Colonie R, Leader JB, Kirchner HL, Murray MF, Reid JG, Carey DJ, Overton JD, Shuldiner AR, Gottesman O, Gao S, Gromada J, Baras A, Altarejos J; Geisinger-Regeneron DiscovEHR collaboration. Clinical and Molecular Prevalence of Lipodystrophy in an Unascertained Large Clinical Care Cohort. Diabetes. 2020; 69(2):249-258. doi: 10.2337/db19-0447\u003c/li\u003e\n \u003cli\u003eFern\u0026aacute;ndez-Pombo A, S\u0026aacute;nchez-Iglesias S, Castro-Pais AI, Ginzo-Villamayor MJ, Cobelo-G\u0026oacute;mez S, Prado-Mora\u0026ntilde;a T, et al. Natural history and comorbidities of generalised and partial lipodystrophy syndromes in Spain. Front Endocrinol. (Lausanne) 2023; 14:1250203. doi: 10.3389/fendo.2023.1250203\u003c/li\u003e\n \u003cli\u003eDonadille B, Janmaat S, Mosbah H, Belalem I, Lamothe S, Nedelcu M, Jannot AS, Christin-Maitre S, F\u0026egrave;ve B, Vatier C, Vigouroux C. Diagnostic and referral pathways in patients with rare lipodystrophy and insulin-resistance syndromes: key milestones assessed from a national reference center. Orphanet J Rare Dis. 2024; 19(1):177. doi: 10.1186/s13023-024-03173-2.\u003c/li\u003e\n \u003cli\u003eLoh WJ, Yaligar J, Hooper AJ, Sadananthan SA, Kway Y, Lim SC, Watts GF, Velan SS, Leow MKS, Khoo J. Clinical and imaging features of women with polygenic partial lipodystrophy: a case series. Nutr. Diabetes. 2024; 14,3 https://doi.org/10.1038/s41387-024-00260-y\u003c/li\u003e\n \u003cli\u003eMann JP, Savage DB. What lipodystrophies teach us about the metabolic syndrome. J Clin Invest. 2019; 129(10):4009-21. doi: 10.1172/JCI129190\u003c/li\u003e\n \u003cli\u003eLim K, Haider A, Adams C, Sleigh A, Savage DB. Lipodistrophy: a paradigm for understanding the consequences of \u0026quot;overloading\u0026quot; adipose tissue. Physiol Rev. 2021; 101(3):907-93. doi: 10.1152/physrev.00032.2020\u003c/li\u003e\n \u003cli\u003eLoh WJ, Johnston DG, Oliver N, Godsland IF. Skinfold thickness measurements and mortality in white males during 27.7 years of follow-up. Int J Obes (Lond). 2018; 42(11):1939-45. doi:10.1038/s41366-018-0034-0\u003c/li\u003e\n \u003cli\u003eNazare JA, Smith JD, Borel AL, Haffner SM, Balkau B, Ross R, Massien C, Alm\u0026eacute;ras N, Despr\u0026eacute;s JP.. Ethnic influences on the relations between abdominal subcutaneous and visceral adiposity, liver fat, and cardiometabolic risk profile: the International Study of Prediction of Intra-Abdominal Adiposity and Its Relationship with Cardiometabolic Risk/Intra-Abdominal Adiposity. Am J Clin Nutr. 2012; 96(4): 714-26. doi: 10.3945/ajcn.112.035758\u003c/li\u003e\n \u003cli\u003eMarfell-Jones MJ, Stewart AD, De Ridder JH. International standards for anthropometric assessment. Wellington, New Zealand: International Society for the Advancement of Kinanthropometry 2012\u003c/li\u003e\n \u003cli\u003eKway YM, Thirumurugan K, Michael N, Tan KH, Godfrey KM, Gluckman P, Chong YS, Venkataraman K, Khoo EYH, Khoo CM, Leow MK, Tai ES, Chan JK, Chan SY, Eriksson JG, Fortier MV, Lee YS, Velan SS, Feng M, Sadananthan SA. A fully convolutional neural network for comprehensive compartmentalization of abdominal adipose tissue compartments in MRI. Comput Biol Med. 2023; 167:107608. doi: 10.1016/j.compbiomed.2023.107608.\u003c/li\u003e\n \u003cli\u003eKrssak M, Lindeboom L, Schrauwen-Hinderling V, Szczepaniak LS, Derave W, Lundborn J, et al., Proton magnetic resonance spectroscopy in skeletal muscle: Experts\u0026apos; consensus recommendations. NMR Biomed. 2021; 34(5): p. e4266. doi: 10.1002/nbm.4266\u003c/li\u003e\n \u003cli\u003eSoh BP, Lee SY, Wong WY, Pang BWJ, Lau LK, Jabbar KA, Seah WT, Chen KK, Srinivasan S, Ng TP, Wee SL. Body composition reference values in Singaporean adults using dual-energy X-ray absorptiometry-The Yishun study. PLoS One. 2022; 17(10):e0276434. doi: 10.1371/journal.pone.0276434\u003c/li\u003e\n \u003cli\u003eGueugneau M, Coudy-Gandilhon C, Th\u0026eacute;ron L, Meunier B, Barboiron C, Combaret L, Taillandier D, Polge C, Attaix D, Picard B, Verney J, Roche F, F\u0026eacute;asson L, Barth\u0026eacute;l\u0026eacute;my JC, B\u0026eacute;chet D. Skeletal muscle lipid content and oxidative activity in relation to muscle fiber type in aging and metabolic syndrome. J Gerotol Ser A Biomed Sci Med Sci. 2015; 70 (5): 566-76. doi: 10.1093/gerona/glu086\u003c/li\u003e\n \u003cli\u003eSimha V, Lanza IR, Dasari S, Klaus KA, Le Brasseur N, Vuckovic I, Laurenti MC, Cobelli C, Port JD, Nair KS. Impaired muscle mitochondrial function in familial partial lipodystrophy. J Clin Endocrinol Metab. 2022; 107(2):346-62. doi: 10.1210/clinem/dgab725\u003c/li\u003e\n \u003cli\u003eEldin AJ, Akinci B, da Rocha AM, Meral R, Simsir IY, Adiyaman SC, Ozpelit E, Bhave N, Gen R, Yurekli B, Ozdemir Kutbay N, Siklar Z, Neidert AH, Hench R, Tayeh MK, Innis JW, Jalife J, Oral H, Oral EA. Cardiac phenotype in familial partial lipodystrophy. Clin Endocrinol. 2021; 94:1043\u0026ndash;1053. doi: 10.1111/cen.14426\u003c/li\u003e\n \u003cli\u003eAjluni N, Meral R, Neidert AH, Brady GF, Buras E, McKenna B, DiPaola F, Chenevert TL, Horowitz JF, Buggs-Saxton C, Rupani AR, Thomas PE, Tayeh MK, Innis JW, Omary MB, Conjeevaram H, Oral EA. Spectrum of disease associated with partial lipodystrophy: lessons from a trial cohort. Clin Endocrinol (Oxf). 2017; 86(5): 698-707. doi: 10.1111/cen.13311.\u003c/li\u003e\n \u003cli\u003eHussain I, Patni N, Garg A. Lipodystrophies, dyslipidaemias and atherosclerotic cardiovascular disease. Pathology. 2019; 51(2):202-12. doi: 10.1016/j.pathol.2018.11.004\u003c/li\u003e\n \u003cli\u003eGuill\u0026iacute;n-Amarelle C, S\u0026aacute;nchez-Iglesias S, Castro-Pais A, Rodriguez-Ca\u0026ntilde;ete L, Ord\u0026oacute;\u0026ntilde;ez-May\u0026aacute;n L, Pazos M, Gonz\u0026aacute;lez-M\u0026eacute;ndez B, Rodr\u0026iacute;guez-Garc\u0026iacute;a S, Casanueva FF, Fern\u0026aacute;ndez-Marmiesse A, Ara\u0026uacute;jo-Vilar D. Type 1 familial partial lipodystrophy: understanding the Kobberling syndrome. Endocrine. 2016; 54(2): 411-21. doi: 10.1007/s12020-016-1002-x.\u003c/li\u003e\n \u003cli\u003eFriedl KE, Westphal KA, Marchitelli LJ., Patton JF, Chumlea WC, Guo SS. Evaluation of anthropometric equations to assess body-composition changes in young women. Am J Clin Nutr. 2001; 73: 268\u0026ndash;75. doi: 10.1093/ajcn/73.2.268. Erratum in: Am J Clin Nutr. 2002; 76(3):695\u003c/li\u003e\n \u003cli\u003ePineau JC, Frey A. Comparison of skinfold thickness models with DEXA: impact of visceral adipose tissue. J Sports Med Phys Fitness. 2016; 56(5):541\u0026ndash;5.\u003c/li\u003e\n \u003cli\u003eMeral R, Ryan BJ, Malandrino N, Jalal A, Neidert AH, Muniyappa R, Akıncı B, Horowitz JF, Brown RJ, Oral EA. \u0026quot;Fat shadows\u0026quot; from DXA for the qualitative assessment of lipodystrophy: when a picture is worth a thousand numbers. Diabetes Care. 2018; 41(10):2255-2258. doi: 10.2337/dc18-0978\u003c/li\u003e\n \u003cli\u003eAgrawal S, Wang M, Klarqvist MDR, Smith K, Shin J, Dashti H, Diamant N, Choi SH, Jurgens SJ, Ellinor PT, Philippakis A, Claussnitzer M, Ng K, Udler MS, Batra P, Khera AV. Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots. Nat Commun. 2022; 13(1):3771. doi: 10.1038/s41467-022-30931-2.\u003c/li\u003e\n \u003cli\u003eValerio CM, Zajdenverg L, de Oliveira JE, Mory PB, Moises RS, Godoy-Matos AF. Body composition study by dual-energy x-ray absorptiometry in familial partial lipodystrophy: finding new tools for an objective evaluation. Diabetol Metab Syndr. 2012; 4(1):40. doi: 10.1186/1758-5996-4-40\u003c/li\u003e\n \u003cli\u003eVasandani C, Li X, Sekizkardes H, Adams-Huet B, Brown RJ, Garg A. Diagnostic value of anthropometric measurements for familial partial lipodystrophy, Dunnigan variety. J Clin Endocrinol Metab. 2020; 105(7): 2132-41. doi: 10.1210/clinem/dgaa137\u003c/li\u003e\n \u003cli\u003eO\u0026apos;Connor L, Brage S, Griffin SJ, Wareham NJ, Forouhi NG. The cross-sectional association between snacking behaviour and measures of adiposity: the Fenland Study, UK. Br J Nutr. 2015; 114(8):1286-93. doi: 10.1017/S000711451500269X.\u003c/li\u003e\n \u003cli\u003eAgrawal S, Luan J, Cummings BB, Weiss EJ, Wareham NJ, Khera AV. Relationship of fat mass ratio, a biomarker for lipodystrophy, with cardiometabolic traits. Diabetes. 2024; 73(7):1099-1111. doi: 10.2337/db23-0575.\u003c/li\u003e\n \u003cli\u003eVeras VR, da Cruz Paiva Lima GE, da Ponte Melo I, Fernandes VO, de Moura Lopes FK, do Amaral CL, Castelo MHG, Queiroz LL, Ara\u0026uacute;jo JS, Valerio CM, Montenegro Junior RM. Anthropometric measurements as a key diagnostic tool for familial partial lipodystrophy in women. Diabetol Metab Syndr. 2024; 16(1):216. doi: 10.1186/s13098-024-01413-w.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"lipodystrophy, metabolic syndrome, DEXA, MRI, case report","lastPublishedDoi":"10.21203/rs.3.rs-6756323/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6756323/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Lipodystrophy, characterized by loss of subcutaneous adipose tissue (SAT) in the limbs, is associated with visceral adiposity and metabolic syndrome. The diagnosis of partial lipodystrophy, with fat loss affecting the legs in the presence of increased abdominal adiposity, is challenging in males due to lack of established criteria and difficulty in differentiating from the normal android pattern of obesity, especially with increasing age. There is a paucity of data in Asian populations, in whom the prevalence of diabetes is increasing and in whom lipodystrophy may be under-recognized.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We describe three men (cases) of Chinese ethnicity and metabolic syndrome with clinical features suspicious of partial lipodystrophy (abdominal obesity and relatively thin lower limbs) who tested negative for Cushing syndrome, and compared their skinfold thickness and other anthropometric measurements, metabolic profile, and body composition using dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI), to a control (an abdominally obese Chinese man of similar age and BMI with metabolic syndrome).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The cases (age 50-51) were borderline obese by BMI (28-30 kg/m2) and abdominally obese (waist circumference WC 98-122 cm) The control was 56 years old with BMI of 31.7 kg/m2 and WC 109 cm. Despite lower BMI of the cases compared to the control, these men had more severe insulin resistance and cardiometabolic outcomes, thinner lower limb skinfolds indicating less subcutaneous fat) higher Android/Gynoid fat ratio (a pattern of body fat distribution that is associated with lipodystrophy and metabolic syndrome), trunk to leg fat mass ratio and ratio of trunk to leg fat percentage (FMR) on DXA, and larger visceral abdominal fat (VAT) depots in association with more pronounced subcutaneous fat wasting in the limbs (higher VAT-to-SAT ratio) on MRI. All cases tested negative for pathogenic variants in monogenic diabetes genes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Our report illustrates the differences in body composition in Chinese men with clinical features of partial lipodystrophy in reference to a control of similar age and BMI. DXA and MRI are useful to characterize adiposity distribution and muscle wasting, and are useful adjunct tools for the diagnosis of partial lipodystrophy in Chinese men with metabolic syndrome.\u003c/p\u003e","manuscriptTitle":"The utility of DXA and MRI for overcoming the limitations of clinical evaluation in diagnosis of partial lipodystrophy in Chinese men with metabolic syndrome: a case series","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-08 06:25:56","doi":"10.21203/rs.3.rs-6756323/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-07-03T09:58:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-02T05:15:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-12T09:53:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-11T10:56:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Endocrine Disorders","date":"2025-06-11T10:24:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"594125e3-3a47-49ab-8733-6718216f6231","owner":[],"postedDate":"July 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-08T06:25:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-08 06:25:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6756323","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6756323","identity":"rs-6756323","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}