Systemic metabolism in frontotemporal dementia

Rebekah M. Ahmed, MBBS Mia MacMillan, BSc Lauren Bartley, BSc Glenda M. Halliday, PhD Matthew C. Kiernan, DSc John R. Hodges, MD Olivier Piguet, PhD

Correspondence to Dr. Piguet: [email protected]


Objective: To document the metabolic changes in frontotemporal dementia, including serum cholesterol and insulin levels, and compare and contrast these changes to motor neuron disease, where metabolism is proposed to affect disease progression.

Methods: A cohort of 90 patients with dementia (31 behavioral-variant frontotemporal dementia [bvFTD], 30 semantic dementia [SD], and 29 Alzheimer disease [AD]) underwent fasting blood cholesterol, glucose, and peripheral insulin level analysis. Insulin resistance was calculated using the homeostasis model assessment of insulin resistance (HOMA-IR). These results were compared with a cohort of 19 control subjects. Results: The bvFTD cohort had lower high-density lipoprotein (HDL) cholesterol levels compared with control and AD groups, and increased total cholesterol/HDL ratio and triglyceride levels compared with the control group. The SD cohort had increased triglyceride levels compared with control subjects. Both FTD groups had increased fasting insulin levels and HOMA-IR index compared with the control group, and this remained increased in the subjects with bvFTD compared to subjects with AD.

Conclusion: Both patients with bvFTD and those with SD have increased triglyceride and insulin levels and lower HDL cholesterol levels compared with controls, suggesting a state of peripheral insulin resistance. These factors have been found to affect prognosis in motor neuron disease favorably, although insulin resistance has been proposed as a mechanism promoting neurodegeneration. We discuss the potential role of metabolism in FTD pathophysiology and progression. Neurology® 2014;83:1812–1818 GLOSSARY ACE-R 5 Addenbrooke’s Cognitive Examination–Revised; AD 5 Alzheimer disease; APEHQ 5 Appetite and Eating Habits Questionnaire; BMI 5 body mass index; bvFTD 5 behavioral-variant frontotemporal dementia; CBI 5 Cambridge Behavioral Inventory; CDR 5 Clinical Dementia Rating; FRS 5 Frontal Rating Scale; FTD 5 frontotemporal dementia; HDL 5 highdensity lipoprotein; HOMA-IR 5 homeostasis model assessment of insulin resistance; LDL 5 low-density lipoprotein; MND 5 motor neuron disease; SD 5 semantic dementia.

Eating abnormalities form one of the major criteria for the diagnosis of behavioral-variant frontotemporal dementia (bvFTD).1 Patients typically develop changes in appetite, binge-eating behavior, and increased carbohydrate and sugar intake.2 Changes in body mass index (BMI) are present in the 2 most common FTD subtypes, bvFTD and semantic dementia (SD),3 but how these eating abnormalities affect other markers of metabolism including lipid and triglyceride levels and peripheral insulin levels is not known. In motor neuron disease (MND), which shares clinical features and a common pathology with FTD,4 a distinct metabolic pattern has been observed including a state of hypermetabolism,5 low BMI,6,7 hyperlipidemia including increased triglyceride levels8 and peripheral insulin resistance.9 These factors have been found to affect disease progression with an increased triglyceride level,10 increased low-density lipoprotein (LDL) to high-density lipoprotein (HDL) ratio,8 and the presence of diabetes mellitus thought to be protective against disease progression.8,9 In contrast, in other forms of progressive neurodegenerative brain conditions, including From Neuroscience Research Australia (R.M.A., M.M., L.B., G.M.H., M.C.K., J.R.H., O.P.), Sydney; Prince of Wales Clinical School (R.M.A., J.R.H.), School of Medical Sciences (G.M.H., O.P.), and ARC Centre of Excellence in Cognition and its Disorders (R.M.A., G.M.H., J.R.H., O.P.), the University of New South Wales, Sydney; and Sydney Medical School (M.C.K.), Brain and Mind Research Institute, University of Sydney, Australia. Go to for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article. 1812

© 2014 American Academy of Neurology

Alzheimer disease (AD),11 Parkinson disease,12 and Huntington disease,13 an increased incidence of insulin resistance and glucose intolerance has been found, which have been suggested to be detrimental, rather than protective, and promote neurodegeneration.14 We aimed to compare the metabolic health (lipid and insulin levels) of a cohort of patients with FTD (bvFTD and SD) to that of patients with AD and healthy controls. We hypothesized that patients with FTD, particularly those with bvFTD, would exhibit abnormalities of their lipid levels and increased insulin levels compared with the other patient groups and compared with controls. METHODS Patients. Ninety patients with dementia (31 bvFTD, 30 SD, 29 AD) were recruited from FRONTIER, the frontotemporal dementia clinic at Neuroscience Research Australia, Sydney. All patients underwent a comprehensive assessment, which included a clinical interview, neurologic examination, cognitive assessment, and structural brain MRI. All patients met the current clinical diagnostic criteria for probable bvFTD, SD, or AD,1,15,16 and diagnosis was established by consensus among the neurologist, neuropsychologist, and occupational therapist. Disease severity was established using the Frontal Rating Scale (FRS).17 The FRS provides logit scores, which are subdivided into 6 categories, ranging from very mild (4.12), mild (4.11–1.92), moderate (1.91–0.40), severe (0.39 to 22.58), very severe (22.57 to 24.99), to profound (below 24.99). Higher scores on the FRS denote higher functioning. In addition, 19 age- and education-matched healthy controls were included in the study. These individuals were either spouses of patients or were recruited from a panel of healthy study volunteers. These volunteers were representative of the socioeconomic spectrum of the Australian population. All healthy controls scored above 88/100 on the Addenbrooke’s Cognitive Examination–Revised (ACE-R)18 and zero on the Clinical Dementia Rating (CDR).19 Exclusion criteria included significant extrapyramidal features, history of stroke, epilepsy, alcoholism, significant traumatic brain injury, or presence of ferrous metal implants in the body. Patients with an uncertain diagnosis, or where a carer was not available, were also excluded from the project. Concomitant diseases and medications. Patients’ records from their local medical officer were obtained to ascertain presence of diabetes or hypercholesterolemia. Current list of medications for treatment with cholesterol (statin) or diabetic medications was also examined. Assessment of physical measurements. Height and weight were measured (shoes removed) and BMI was derived (unit: kg/m2). Assessment of eating behavior. Carers completed the Appetite and Eating Habits Questionnaire (APEHQ) and the Cambridge Behavioral Inventory (CBI).20 The APEHQ comprises 34 questions that examine changes in eating behaviors in the following domains: swallowing, appetite, eating habits (stereotypic eating behavior and table manners), food preference (including sweet preference and other food fads), and other oral behaviors (food cramming, increased smoking, etc.). Carers were asked to rate the frequency on a 5-point Likert scale, ranging from 0 (never) to 4 (daily or continuously), and severity on a 4-point Likert scale, ranging from 0 (not applicable) to 3 (marked) for

each behavior. A composite score of frequency 3 severity was calculated for each question and an overall score was calculated. The 4 questions from the CBI specifically related to eating behavior (sweet preference, same foods, change in appetite, and table manners) were also analyzed. Each CBI item was rated using a 5-point Likert scale ranging from 0 (never) to 4 (constantly).

Blood measurements. Blood samples were obtained from all participants after a 10-hour fast. Measurement of cholesterol levels. Total cholesterol, triglyceride, and HDL levels were measured using the enzymatic colorimetric method using Cobas 8000, supplied by Roche diagnostics (Indianapolis, IN). LDL levels were calculated using the Friedewald formula: LDL 5 (cholesterol 2 [triglyceride/2.2]) 2 HDL. Measurement of insulin levels. Fasting serum insulin was measured using ELISA (Mercodia, Uppsala, Sweden). Absorption was determined using a microplate reader (POLARstar Omega; BMG Labtech, Ortenberg, Germany) at a wavelength of 450 nm. Insulin resistance. Insulin resistance was calculated using the homeostasis model assessment of insulin resistance (HOMAIR)21,22 using the following formula: fasting serum insulin (mU/L) 3 fasting plasma glucose (mmol/L)/22.5. Low HOMA-IR values indicate high insulin sensitivity, whereas high HOMA-IR values indicate low insulin sensitivity (insulin resistance). Standard protocol approvals, registrations, and patient consents. This study was approved by the South Eastern Sydney and Illawarra Area Health Service and the University of New South Wales human ethics committees. Written informed consent was obtained from the participant and/or primary carer.

Data analysis. Data were analyzed using IBM SPSS statistics (version 21.0; IBM Corp., Armonk, NY). Kolmogorov–Smirnov tests were run to determine suitability of variables for parametric analyses. Analyses of variance, followed by Tukey post hoc tests, were used to explore main effects of group (controls, bvFTD, SD, and AD) for the variables age and total ACE scores (p , 0.05 regarded as significant). BMI, FRS scores, total cholesterol, HDL, LDL, and triglyceride levels, insulin levels, HOMA-IR index (insulin resistance), and glucose levels were analyzed using Kruskal–Wallis tests followed by post hoc Mann–Whitney tests corrected for multiple comparisons (p , 0.01 regarded as significant). Spearman correlations were also performed to examine the relations of cholesterol and insulin levels with BMI and total score on the APEHQ. The metabolic variables were also correlated with the FRS scores. Differences in frequency patterns of categorical variables (e.g., occurrence of diagnosis of diabetes and hypercholesterolemia and treatment with anticholesterol and diabetic medications, and sex) were examined with x2 tests and post hoc Fisher exact tests (p , 0.05 regarded as significant).

The 2 FTD groups were well matched for all demographic characteristics (table 1). Other group comparisons showed that disease duration was shorter in the AD than the bvFTD group (p 5 0.027) and that the control group was slightly older than the bvFTD group (p 5 0.018). The bvFTD group had a lower FRS score suggesting increased disease severity compared with the AD (p , 0.001) and SD groups (p 5 0.002). Not surprisingly, the control group scored higher than the patient groups on the ACE-R, a measure of global cognition (p , 0.001), with the SD also scoring lower than the bvFTD group RESULTS

Neurology 83

November 11, 2014


Table 1

Demographic characteristics and cognitive scores for the dementia and control groups

Sex, F/M





F value

Post hoc test






NA a

Age, y

63 6 9.1

66 6 6.1

67 6 7.6

69 6 4.2


Disease duration, y

6.2 6 2.9

5.4 6 2.0

4.4 6 2.4



78 6 11.3

ACE-R total (100)

11.7 6 6.5

CBI abnormal behaviors Clinical Dementia Rating FRS logit scores

63 6 14.8 6.6 6 6.1

71 6 15.4

95 6 4.3

3.7 6 3.5


Controls . bvFTD bvFTD . AD



Controls . patient groups, bvFTD . SD



bvFTD . AD, SD


1.4 6 0.8

0.8 6 0.5

0.9 6 0.4



bvFTD . AD, SD; patient groups . controls

20.8 6 1.1

0.9 6 1.4

0.4 6 1.5



bvFTD . AD, SD

Abbreviations: ACE-R 5 Addenbrooke’s Cognitive Examination–Revised; AD 5 Alzheimer disease; bvFTD 5 behavioral-variant frontotemporal dementia; CBI 5 Cambridge Behavioral Inventory; FRS 5 Frontal Rating Scale; NA 5 not applicable; NS 5 not significant; SD 5 semantic dementia. a p , 0.05. b p , 0.001. c Kruskal–Wallis H value. Data presented as mean 6 standard deviation.

(p , 0.001) because of the language component of the task. On the CBI abnormal behavior subscale, the bvFTD group scored higher than the SD and AD groups. On the global CDR, a group difference was present, with all patient groups obtaining a higher score than controls. In addition, global CDR was higher in the bvFTD than in the AD (p 5 0.021) and the SD (p 5 0.005) groups. BMI and concomitant disease and medications. BMI differed across groups (table 2). The bvFTD and SD groups had a higher BMI than the control group (p 5 0.001). Groups did not differ regarding the prevalence of previously diagnosed hypercholesterolemia or in the frequency of treatment with a statin. Presence of diabetes differed across groups, with the bvFTD group having a higher prevalence than the control (p 5 0.042) and SD (p 5 0.001) groups. Eating behavior. Examining eating habits and behavior, analyses showed that the bvFTD group had higher abnormal behavior on the APEHQ compared with the AD (p , 0.001) and SD (p 5 0.001) groups (table 3). The SD group also had a higher score than the AD group (p 5 0.010). On the CBI eating

Table 2

questions, the bvFTD group had significant abnormalities in sweet preference, food preference, and table manners compared with the AD group, and in sweet preference, food preference, and appetite compared with the SD group (all p values ,0.01) (table 3). Cholesterol and triglyceride levels. No group differences were found across groups for total cholesterol levels (normal range: 3.0–5.5 mmol/L) (p 5 0.991) or for LDL cholesterol levels (normal level: ,3.5 mmol/L) (p 5 0.703) (figure 1). In contrast, HDL cholesterol levels (normal range: 0.9–2.4 mmol/L) differed across groups (p 5 0.001), with the bvFTD group exhibiting a lower HDL cholesterol level (mean 5 1.3 mmol/L) compared with the control (mean 5 2.0 mmol/L; p , 0.001) and AD (mean 5 1.8 mmol/L; p 5 0.004) groups. A group difference was also found for the total cholesterol to HDL ratio (p 5 0.001), with bvFTD showing an increased ratio (mean 5 4.55 mmol/L) compared with controls (mean 5 2.87 mmol/L; p 5 0.001). No other differences among patient groups were present. Group differences were found on analysis of triglyceride levels (normal level: ,2 mmol/L) (p , 0.01).

BMI and frequency of patients with diagnosis of hypercholesterolemia, diabetes, and associated treatments bvFTD




x2/H value

Post hoc test

BMI, mean 6 standard deviation

29.6 6 5.0

27.3 6 4.9

26.7 6 6.0

24.4 6 3.2


bvFTD . controls, SD . controls

Hypercholesterolemia, present/not present






NS a

Diabetes, present/not present






Statin treatment, present/not present






Antidiabetic treatment (metformin), present/not present







bvFTD . controls, SD NS bvFTD . AD, SD

Abbreviations: AD 5 Alzheimer disease; BMI 5 body mass index; bvFTD 5 behavioral-variant frontotemporal dementia; NS 5 not significant; SD 5 semantic dementia. a p , 0.001. 1814

Neurology 83

November 11, 2014

Table 3

APEHQ and CBI results in the patient groups

bvFTD APEHQ total



Kruskal–Wallis H value a

Post hoc

59.2 6 34.5

28.8 6 31.3

13.9 6 21.2


2.4 6 1.5

1.1 6 1.5

0.9 6 1.2


bvFTD . AD, SD

0.5 6 0.9



bvFTD . AD, SD


bvFTD . SD bvFTD . AD

bvFTD . AD, SD; SD . AD

CBI Sweet preference Same foods

2.0 6 1.7

0.9 6 1.5


1.6 6 1.7

0.4 6 0.9

0.5 6 1.0


Table manners

1.2 6 1.6

0.6 6 0.9

0.1 6 0.3


Abbreviations: AD 5 Alzheimer disease; APEHQ 5 Appetite and Eating Habits Questionnaire; bvFTD 5 behavioral-variant frontotemporal dementia; CBI 5 Cambridge Behavioral Inventory; SD 5 semantic dementia. a p , 0.001. Data presented as mean 6 standard deviation. Note that high scores denote increased abnormal features. For the APEHQ, the overall score reflects the combination of frequency and severity of each relevant feature investigated by the questionnaire.

Post hoc tests showed that the bvFTD group (mean 5 1.9 mmol/L; p , 0.001) and the SD group (mean 5 1.4 mmol/L; p 5 0.004) had increased triglyceride levels compared with the control group (mean 5 0.85 mmol/L). Insulin, glucose, and insulin resistance levels. Fasting insulin levels differed across groups (p , 0.001), with the level in the bvFTD (mean 5 12.2 mU/L) being higher compared with control (mean 5 6.1 mU/L; p , 0.001), AD (mean 5 8.6 mU/L; p 5 0.002), and SD (mean 5 9.6 mU/L; p 5 0.005) groups (figure 2A). Fasting insulin levels were also higher in the SD group compared with controls (p , 0.001). In contrast, no group differences were found for fasting serum glucose levels (p 5 0.402). A group difference was found for the HOMA-IR index (normal population value for age-matched

Figure 1

controls: 1.9; range: 1.4–2.9)21,22 (p , 0.001) (figure 2B), with the bvFTD group showing a higher index (mean 5 3.5) compared with the control (mean 5 1.5; p , 0.001), AD (mean 5 2.2; p 5 0.005), and SD (mean 5 2.3; p 5 0.005) groups. The SD group also had an increased HOMA-IR index compared with the control group (p 5 0.006). Correlations. The total APEHQ score and BMI were correlated to markers of metabolic health. Positive correlations were found between the APEHQ and triglyceride levels (rs 5 0.337, p 5 0.002) and HOMAIR (rs 5 0.367, p 5 0.002). BMI was also positively correlated with triglyceride levels (rs 5 0.444, p , 0.001) and with the HOMA-IR (rs 5 0.579, p , 0.001). In contrast, HDL cholesterol values were negatively correlated with APEHQ total score (rs 5 20.339, p , 0.001) and with BMI (rs 5 20.601,

Cholesterol and triglyceride levels in the patient groups

(A) Total cholesterol, LDL cholesterol, and total cholesterol to HDL cholesterol ratio in patient groups: * bvFTD . control (p 5 0.001). (B) Triglyceride and total HDL cholesterol levels: ** bvFTD . control (p , 0.001); *** SD . control (p 5 0.004); **** bvFTD , control and AD (p , 0.01). AD 5 Alzheimer disease; bvFTD 5 behavioral-variant frontotemporal dementia; HDL 5 high-density lipoprotein; LDL 5 low-density lipoprotein; SD 5 semantic dementia. Neurology 83

November 11, 2014


Figure 2

Fasting insulin levels and HOMA-IR index

(A) Fasting insulin and glucose levels in patients groups: * bvFTD . control, AD, and SD (p , 0.01); ** SD . control (p , 0.001). (B) HOMA-IR index in patients groups: *** bvFTD . control, AD, and SD (p , 0.01); **** SD . control (p , 0.01). AD 5 Alzheimer disease; bvFTD 5 behavioral-variant frontotemporal dementia; HOMA-IR 5 homeostasis model assessment of insulin resistance; SD 5 semantic dementia.

p , 0.001). In addition, metabolic health was also associated with disease progression: FRS scores were positively correlated with HDL cholesterol levels (rs 5 0.321, p 5 0.003) and negatively associated with triglyceride levels (rs 5 20.214, p 5 0.048). No association was observed between the HOMAIR index and FRS logit scores. This study examined the systemic metabolic health in FTD. We uncovered changes in triglyceride and HDL cholesterol levels and a state of peripheral insulin resistance in bvFTD and SD, as well as an increased prevalence of diabetes mellitus in patients with bvFTD in keeping with the finding of peripheral insulin resistance. These changes were most marked in the bvFTD group who had increased triglyceride levels, lower HDL cholesterol levels, and an increased total cholesterol to HDL cholesterol ratio compared with controls. The patients with bvFTD also experienced increased fasting peripheral insulin levels and an HOMA-IR index of 3.5 compared with 1.5 in controls and 2.2 in patients with AD, suggesting a state of peripheral insulin resistance. Elevated triglyceride levels and HOMAIR index were also observed in SD, again suggesting a state of peripheral insulin resistance in this group. Previous studies in adult populations21 of a similar age to our patient groups have found an HOMA-IR index of 1.9 (range 1.4–2.9), a level lower than those observed in our bvFTD (3.5) and SD (2.3) cohorts. A number of variables are likely to contribute to these results. The abnormal eating behavior in FTD, particularly bvFTD, is well documented,2,23 with patients exhibiting binge-eating behavior, sweet preference, and increased carbohydrate intake.2 In the current study, the 2 groups with the greatest abnormalities on the APEHQ (i.e., bvFTD and SD) DISCUSSION


Neurology 83

November 11, 2014

exhibited a high BMI, and marked changes in HDL cholesterol, triglyceride, and insulin levels. These metabolic variables were also associated with changes in eating habits, as reported by caregivers, and with BMI. These results suggest that abnormal eating coupled with high BMI contribute partly to these changes. The high triglyceride levels and low HDL cholesterol levels in bvFTD provide further evidence of a state of insulin resistance, similar to that observed in obese men with high triglyceride and low HDL cholesterol levels associated with hyperinsulinemia and the metabolic syndrome.24 Eating behavior abnormalities and high BMI, however, are unlikely to be solely responsible for the abnormalities in FTD, with other variables likely contributing to the insulin resistance, including the process of neurodegeneration itself. Hyperlipidemia,8,10 abnormal glucose metabolism, and insulin resistance9,25 have been demonstrated in patients with MND, which shares a common pathology with a high proportion of patients with FTD.4 Patients with MND have abnormalities in lipid, triglyceride, and insulin levels despite typically having a low BMI.7,26 Blood lipid abnormalities, including an elevated LDL cholesterol to HDL ratio,8 low HDL,8 and elevated triglyceride levels (median 1.47 mmol/ L),10 have been found in MND. It has been suggested that these variables may modulate disease progression and prognosis, whereby increased lipid and triglyceride levels10 are associated with improved survival.6,8,10,27 Indeed, treatment with statins, which lower lipid levels, results in a worse outcome in patients with MND.28 Insulin resistance has also been documented in MND,25,29 with the suggestion that its presence may delay disease onset in individuals with preexisting diabetes mellitus.9 A recent phase II clinical trial in MND with pioglitazone, an antidiabetic

medication, resulted in an increase in mortality.30 The mechanisms underlying changes in lipid levels and insulin resistance and how these may be protective in MND are not understood.6 One hypothesis is that patients with MND increase their energy intake in order to compensate for a state of hypermetabolism,5,31–34 which then results in increased lipid levels and a state of insulin resistance.6 In contrast to the findings in MND, a role for insulin and increased peripheral insulin resistance and diabetes in the process of neurodegeneration has been found in dementia,35 AD,11 Parkinson disease,12 and Huntington disease.13,36 How insulin promotes neurodegeneration is not clear, but is likely to have effects both peripherally and centrally. Proposed mechanisms include the promotion of oxidative stress, inflammation, vascular dysfunction, and impairment of neurogenesis and neuronal repair.14 In AD, high peripheral insulin levels may inhibit b-amyloid degradation and decrease the number of insulin receptors at the bloodbrain barrier leading to lower concentrations of insulin in the brain. Insulin inhibits the phosphorylation of tau and thus a low brain insulin concentration could lead to the hyperphosphorylation of tau and the formation of neurofibrillary tangles.14 How insulin is potentially involved in the pathogenesis of FTD has not been examined, but given the potential role of insulin resistance in other neurodegenerative diseases, it is worthy of further investigation. The role of lipids and the development of dementia and mild cognitive impairment has received attention.37 Several studies have found that hypertriglyceridemia and low HDL cholesterol are associated with the development of mild cognitive impairment.37,38 The use of statins39 has been associated with a lower incidence of dementia and cognitive impairment. Again, the role of lipids and in particular triglycerides and HDL cholesterol, which we have shown to have changes in FTD, requires further investigation to understand the impact on the pathogenesis of FTD. FTD provides an interesting model in which to establish the effects of metabolic parameters on disease development and pathophysiology with 2 emerging avenues. On the one hand, given the strong overlap between MND and FTD, and the potential protective effect of hyperinsulinemia and hyperlipidemia in MND, it is possible that these variables may also be protective in FTD. On the other hand, however, lipids and hyperinsulinemia have a documented potential role in neurodegeneration and may be detrimental in FTD. One unifying hypothesis is that hyperinsulinemia and lipid changes may be peripherally protective in terms of muscle metabolism, but centrally detrimental in terms of cognitive function. In MND, increasing evidence indicates involvement of peripheral and central nervous systems, even in the pure lower motor

neuron forms of the disease.40 It is therefore plausible that, peripherally, metabolic variables overcome some of the central detrimental effects, for a net protective balance. These explanations offer the potential to modify disease progression and prognosis and help in understanding and delineating the spectrum of FTD and MND. Ideally, longitudinal studies on presymptomatic individuals with genetic mutations examining aspects such as lifestyle, sleep, and physical activity will be conducted to firmly establish the role of metabolic variables in FTD. The high rate of diabetes in the bvFTD cohort uncovered in our study and the documented insulin resistance indicate that monitoring of metabolic parameters may be recommended in FTD. Currently, based on the available evidence, patients with bvFTD with no indication of MND should be advised to monitor their intake and consider treatment if they develop insulin resistance and diabetes. Further research is required to determine how treatment with statins and antidiabetic drugs modifies the disease course in FTD. AUTHOR CONTRIBUTIONS Rebekah Ahmed: data analyses, statistical analysis, manuscript preparation and writing. Mia MacMillan: blood analyses, manuscript preparation and writing. Lauren Bartley: data acquisition and manuscript preparation. Glenda Halliday: data analyses, study concept, manuscript preparation. Matthew Kiernan: manuscript preparation and writing, study concept. John R. Hodges: manuscript preparation and writing, study concept. Olivier Piguet: manuscript preparation and writing, study concept.

STUDY FUNDING This work was supported by funding to ForeFront, a collaborative research group dedicated to the study of frontotemporal dementia and motor neuron disease, from the National Health and Medical Research Council of Australia (NHMRC) program grant (1037746) and the Australian Research Council Centre of Excellence in Cognition and its Disorders Memory Node (CE110001021) and other grants/sources (NHMRC project grant 1003139). The authors are grateful to the research participants involved with the ForeFront research studies. R.A. is a Royal Australasian College of Physicians PhD scholar and MND Australia PhD scholar. G.H. is an NHMRC Senior Principal Research Fellow (630434). O.P. is an NHMRC Career Development Research Fellow (1022684).

DISCLOSURE R. Ahmed, M. MacMillan, L. Bartley, and G. Halliday report no disclosures relevant to the manuscript. M. Kiernan is Editor of the Journal of Neurology, Neurosurgery & Psychiatry. J. Hodges and O. Piguet report no disclosures relevant to the manuscript. Go to for full disclosures.

Received June 24, 2014. Accepted in final form August 8, 2014. REFERENCES 1. Rascovsky K, Hodges JR, Knopman D, et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 2011;134:2456–2477. 2. Ikeda M, Brown J, Holland AJ, Fukuhara R, Hodges JR. Changes in appetite, food preference, and eating habits in frontotemporal dementia and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2002;73:371–376. Neurology 83

November 11, 2014











12. 13. 14.





19. 20.



Ahmed RM, Irish M, Kam J, et al. How many spoonfuls of sugar: quantifying the eating abnormalities in frontotemporal dementia. JAMA Neurol (in press 2014). Clark CM, Forman MS. Frontotemporal lobar degeneration with motor neuron disease: a clinical and pathological spectrum. Arch Neurol 2006;63:489–490. Desport JC, Torny F, Lacoste M, Preux PM, Couratier P. Hypermetabolism in ALS: correlations with clinical and paraclinical parameters. Neurodegener Dis 2005;2:202–207. Dupuis L, Pradat PF, Ludolph AC, Loeffler JP. Energy metabolism in amyotrophic lateral sclerosis. Lancet Neurol 2011;10:75–82. Jawaid A, Murthy SB, Wilson AM, et al. A decrease in body mass index is associated with faster progression of motor symptoms and shorter survival in ALS. Amyotroph Lateral Scler 2010;11:542–548. Dupuis L, Corcia P, Fergani A, et al. Dyslipidemia is a protective factor in amyotrophic lateral sclerosis. Neurology 2008;70:1004–1009. Jawaid A, Salamone AR, Strutt AM, et al. ALS disease onset may occur later in patients with pre-morbid diabetes mellitus. Eur J Neurol 2010;17:733–739. Dorst J, Kuhnlein P, Hendrich C, Kassubek J, Sperfeld AD, Ludolph AC. Patients with elevated triglyceride and cholesterol serum levels have a prolonged survival in amyotrophic lateral sclerosis. J Neurol 2011;258: 613–617. Arvanitakis Z, Wilson RS, Bienias JL, Evans DA, Bennett DA. Diabetes mellitus and risk of Alzheimer disease and decline in cognitive function. Arch Neurol 2004; 61:661–666. Sandyk R. The relationship between diabetes mellitus and Parkinson’s disease. Int J Neurosci 1993;69:125–130. Petersen A, Bjorkqvist M. Hypothalamic-endocrine aspects in Huntington’s disease. Eur J Neurosci 2006;24:961–967. Craft S, Watson GS. Insulin and neurodegenerative disease: shared and specific mechanisms. Lancet Neurol 2004;3:169–178. Gorno-Tempini ML, Hillis AE, Weintraub S, et al. Classification of primary progressive aphasia and its variants. Neurology 2011;76:1006–1014. McKhann GM, Albert MS, Grossman M, et al. Clinical and pathological diagnosis of frontotemporal dementia: report of the Work Group on Frontotemporal Dementia and Pick’s Disease. Arch Neurol 2001;58:1803–1809. Mioshi E, Hsieh S, Savage S, Hornberger M, Hodges JR. Clinical staging and disease progression in frontotemporal dementia. Neurology 2010;74:1591–1597. Mioshi E, Dawson K, Mitchell J, Arnold R, Hodges JR. The Addenbrooke’s Cognitive Examination Revised (ACE-R): a brief cognitive test battery for dementia screening. Int J Geriatr Psychiatry 2006;21:1078–1085. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993;43:2412–2414. Bozeat S, Gregory CA, Ralph MA, Hodges JR. Which neuropsychiatric and behavioural features distinguish frontal and temporal variants of frontotemporal dementia from Alzheimer’s disease? J Neurol Neurosurg Psychiatry 2000; 69:178–186. Soriguer F, Colomo N, Valdes S, et al. Modifications of the homeostasis model assessment of insulin resistance index with age. Acta Diabetol Epub 2014 Apr 1.

Neurology 83

November 11, 2014

22. 23.










33. 34.







Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004;27:1487–1495. Whitwell JL, Sampson EL, Loy CT, et al. VBM signatures of abnormal eating behaviours in frontotemporal lobar degeneration. Neuroimage 2007;35:207–213. Lemieux I, Lamarche B, Couillard C, et al. Total cholesterol/HDL cholesterol ratio vs LDL cholesterol/HDL cholesterol ratio as indices of ischemic heart disease risk in men: the Quebec Cardiovascular Study. Arch Intern Med 2001;161:2685–2692. Reyes ET, Perurena OH, Festoff BW, Jorgensen R, Moore WV. Insulin resistance in amyotrophic lateral sclerosis. J Neurol Sci 1984;63:317–324. Reich-Slotky R, Andrews J, Cheng B, et al. Body mass index (BMI) as predictor of ALSFRS-R score decline in ALS patients. Amyotroph Lateral Scler Frontotemporal Degener 2013;14:212–216. Chio A, Calvo A, Ilardi A, et al. Lower serum lipid levels are related to respiratory impairment in patients with ALS. Neurology 2009;73:1681–1685. Zinman L, Sadeghi R, Gawel M, Patton D, Kiss A. Are statin medications safe in patients with ALS? Amyotroph Lateral Scler 2008;9:223–228. Pradat PF, Bruneteau G, Gordon PH, et al. Impaired glucose tolerance in patients with amyotrophic lateral sclerosis. Amyotroph Lateral Scler 2010;11:166–171. Jawaid A, Paganoni S, Hauser C, Schulz PE. Trials of antidiabetic drugs in amyotrophic lateral sclerosis: proceed with caution? Neurodegener Dis 2014;13:205–208. Desport JC, Preux PM, Magy L, et al. Factors correlated with hypermetabolism in patients with amyotrophic lateral sclerosis. Am J Clin Nutr 2001;74:328–334. Funalot B, Desport JC, Sturtz F, Camu W, Couratier P. High metabolic level in patients with familial amyotrophic lateral sclerosis. Amyotroph Lateral Scler 2009;10:113–117. Kiernan MC, Vucic S, Cheah BC, et al. Amyotrophic lateral sclerosis. Lancet 2011;377:942–955. Turner MR, Hardiman O, Benatar M, et al. Controversies and priorities in amyotrophic lateral sclerosis. Lancet Neurol 2013;12:310–322. Ott A, Stolk RP, van Harskamp F, Pols HA, Hofman A, Breteler MM. Diabetes mellitus and the risk of dementia: the Rotterdam Study. Neurology 1999;53:1937–1942. Lalic NM, Maric J, Svetel M, et al. Glucose homeostasis in Huntington disease: abnormalities in insulin sensitivity and early-phase insulin secretion. Arch Neurol 2008;65: 476–480. Frisardi V, Solfrizzi V, Seripa D, et al. Metabolic-cognitive syndrome: a cross-talk between metabolic syndrome and Alzheimer’s disease. Ageing Res Rev 2010;9:399–417. Panza F, Frisardi V, Capurso C, et al. Metabolic syndrome and cognitive impairment: current epidemiology and possible underlying mechanisms. J Alzheimers Dis 2010;21: 691–724. Cramer C, Haan MN, Galea S, Langa KM, Kalbfleisch JD. Use of statins and incidence of dementia and cognitive impairment without dementia in a cohort study. Neurology 2008;71:344–350. Vucic S, Kiernan MC. Abnormalities in cortical and peripheral excitability in flail arm variant amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2007;78: 849–852.

Systemic metabolism in frontotemporal dementia Rebekah M. Ahmed, Mia MacMillan, Lauren Bartley, et al. Neurology 2014;83;1812-1818 Published Online before print October 10, 2014 DOI 10.1212/WNL.0000000000000993 This information is current as of October 10, 2014 Updated Information & Services

including high resolution figures, can be found at:


This article cites 38 articles, 13 of which you can access for free at:

Subspecialty Collections

This article, along with others on similar topics, appears in the following collection(s): Amyotrophic lateral sclerosis _ Endocrine Frontotemporal dementia

Permissions & Licensing

Information about reproducing this article in parts (figures,tables) or in its entirety can be found online at:


Information about ordering reprints can be found online:

Neurology ® is the official journal of the American Academy of Neurology. Published continuously since 1951, it is now a weekly with 48 issues per year. Copyright © 2014 American Academy of Neurology. All rights reserved. Print ISSN: 0028-3878. Online ISSN: 1526-632X.

Systemic metabolism in frontotemporal dementia.

To document the metabolic changes in frontotemporal dementia, including serum cholesterol and insulin levels, and compare and contrast these changes t...
434KB Sizes 0 Downloads 14 Views